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Contract No.: 282-98-0021MPR Reference No.: 8687-300

2000 Health Care Survey of DoD Beneficiaries: Child Codebook and User’s Guide

December 2001

Final

Submitted to:

TRICARE Management Activity5111 Leesburg Pike, Suite 810Falls Church, VA 22041(703) 681-4263

Task Order Officer:LTC Thomas V. Williams, Ph.D.

Submitted by:

Mathematica Policy Research, Inc.600 Maryland Ave., SW, Suite 550Washington, DC 20024-2512(202) 484-9220

Project Director:Eric Schone, Ph.D.

2000 ANNUAL HEALTH CARE SURVEY OF DOD BENEFICIARIES

PAGE IS INTENTIONALLY LEFT BLANK TO ALLOW FOR DOUBLE-SIDED COPYING

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Contents

Lists Page

Table of Variables............................................................................................................... v

Alphabetical Table of Variables............................................................................................xi

Chapters

1 Introduction........................................................................................................................1

2 Description of the HCSDB Child Database............................................................................5

3 Programming Guide............................................................................................................9

- How to Make a Table Using SAS...................................................................................9- How to Make a Table Using SPSS...............................................................................34- Calculating Variances of Estimates...............................................................................84

4 Codebook........................................................................................................................ 89

Appendices

A Annotated Questionnaire................................................................................................A-1

B Crosswalk for 1999 and 2000 Child Questionnaires........................................................B-1

C Data Quality Coding Scheme and Coding Tables...........................................................C-1

D SAS Proc Contents -- Alphabetical Child 2000..................................................................D-1

E SAS Proc Contents -- Positional Child 2000....................................................................E-1

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Table of Variables

Page

SAMPLING VARIABLESMPRID -Unique MPR Identifier..................................................................................... 89MPCSMPL -MPCSMPL - Military Personnel Category......................................................... 89SVCSMPL -SVCSMPL - Branch of Service........................................................................ 89SEXSMPL -SEXSMPL - Sex............................................................................................ 89AGESMPL -AGESMPL - Age............................................................................................ 90BGCSMPL -BGCSMPL - Beneficiary Group....................................................................... 90REGSMPL -REGSMPL - Region....................................................................................... 90ENBGSMPL -Enrollment by beneficiary category................................................................... 91STRATUM -Sampling STRATUM...................................................................................... 91SUPREG -SUPREG - Super Region................................................................................ 92MRTLSTAT -Marital Status................................................................................................. 92RACEETHN -Race/Ethnic Code.......................................................................................... 92

DEERS VARIABLES

DAGEQY -Age (As of 31 January 2001)........................................................................... 92FIELDAGE -Age (As of 1 July 2001)................................................................................... 93PCM -Primary Manager Code (CIV or MIL)................................................................ 93TSPSITE -TSP Site (regardless of age)........................................................................... 93LEGDDSCD -DDS Code..................................................................................................... 94PNLCATCD -Personnel Category Code (Duty Status)........................................................... 94MBRRELCD -Member Relationship Code............................................................................. 94DBENCAT -Beneficiary Category...................................................................................... 95DMEDELG -Medical Privlege Code.................................................................................... 95DSPONSVC -Derived Sponsor Branch of Service.................................................................. 95MEDTYPE -Medicare Type............................................................................................... 96PATCAT -Aggregated Beneficiary Category..................................................................... 96ENRID -Enrollment DMISID......................................................................................... 96DCATCH -Catchment Area............................................................................................. 101ULOCDMIS -Unit DMISID.................................................................................................. 103ENLSMPL -ENLSMPL - Enrollment Sampling Group.......................................................... 105FNSTATUS -Final Status.................................................................................................... 105KEYCOUNT -# of Key Questions Answered.......................................................................... 106POSTSTR -Post Stratification Cell..................................................................................... 106

QUESTIONNAIRE RESPONSES

C00001 -Are you adult responsible for child.................................................................... 107C00002 -Which hlth plan did you use most..................................................................... 107C00003 -In last 12 mos,# mos in a row cvrd w/Pln.......................................................... 107C00004A -Child covered by TRICARE Prime................................................................... 108C00004B -Child covered by TRICARE Extra/Standard...................................................... 108C00004C -Child covered by Fed. EMP Health Benefit....................................................... 108C00004D -Child covered by Medicaid............................................................................... 108C00004E -Child covered by Civilian HMO......................................................................... 108C00004F -Child covered by Other Civilian Ins................................................................... 109C00004G -Child covered by USFP................................................................................... 109C00004H -Not sure who Child covered by........................................................................ 109C00004I -Child did not use health plan last 12mos........................................................... 109C00005 -Does child have personal Dr/Nurse.................................................................. 109C00006 -How much prblem to get personal Dr/Nurse...................................................... 110C00007 -Talk about feeling/growing/behaving................................................................. 110C00008 -Rating of childs personal Dr/Nurse................................................................... 110

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C00009 -Does child have primary care manager............................................................. 111C00010 -Know name of childs Primary care mgr............................................................ 111C00011 -In last 12 mos how much prblm to see PCM..................................................... 111C00012 -Is primary care mgr military or civilian............................................................... 112C00013 -Did you think child needed to see spclst............................................................ 112C00014 -How much prblm to get referral to spclst........................................................... 112C00015 -In last 12 mos did child see specialist............................................................... 112C00016 -Rating of specialist seen most often................................................................. 113C00017 -Specialist same as personal Dr........................................................................ 113C00018 -Call during reg. Hrs to get help/advice.............................................................. 113C00019 -Called during reg Hrs did you get hlp................................................................ 114C00020 -Make appt for regular/routine hlthcre................................................................ 114C00021 -How oftn get appt for care soon as wnted......................................................... 114C00022 -Wait btwn mking appt and seeing provider........................................................ 115C00023 -Have illness/injury need care right away........................................................... 115C00024 -Get needed care as soon as wanted................................................................ 115C00025 -Wait btwn trying to & seeing provider................................................................ 116C00026 -Appointment for well-patient care..................................................................... 116C00027 -Get appt for well-patient care........................................................................... 116C00028 -Wait to see provider for well-patnt care............................................................. 117C00029 -Times to ER................................................................................................... 117C00030 -Times to Dr office/Clinic (excluding ER)............................................................ 117C00031 -Problem to get necessary care........................................................................ 118C00032 -Problem wait for approval................................................................................ 118C00033 -How oftn wait >15 mins................................................................................... 118C00034 -How oftn staff treat w/courtesy &respect........................................................... 119C00035 -How oftn were staff helpful.............................................................................. 119C00036 -How oftn did staff listen carefully...................................................................... 119C00037 -How oftn did staff explain things to you............................................................. 120C00038 -How oftn staff respect what had to say............................................................. 120C00039 -Child old enough to talk to Dr........................................................................... 120C00040 -Dr explain in way for child to undrstnd............................................................... 121C00041 -How oftn spend enough time w/child................................................................ 121C00042 -Rating of childs healthcare.............................................................................. 122C00043 -Type of facility child used most often................................................................ 122C00044 -Send in any claims......................................................................................... 122C00045 -Handle claim in reasonable time...................................................................... 123C00046 -Handle claim correctly..................................................................................... 123C00047 -Plan make clear how much to pay.................................................................... 123C00048 -Look for info/written material............................................................................ 124C00049 -Find/understand info in written material............................................................. 124C00050 -Call customer service to get info...................................................................... 124C00051 -Problem get help when call customer svc......................................................... 124C00052 -Called/written plan with complaint..................................................................... 125C00053 -How long to resolve complaint......................................................................... 125C00054 -Complaint/problem settled to satisfction............................................................ 125C00055 -Experience with paperwork.............................................................................. 125C00056 -Problem with paperwork.................................................................................. 126C00057 -Rating of exprience with child hlth plan............................................................. 126C00058 -Rate child overall health.................................................................................. 126C00059 -Child use medicine prescribed by Dr................................................................ 127C00060 -Medicine b/c medical,behavioral,other.............................................................. 127C00061 -Medicine b/c cndtn expected last>=12 mos....................................................... 127C00062 -Mre medical,mntl,edcution svcs thn usual......................................................... 127C00063 -Use svcs b/c medical, behavioral, oth............................................................... 128C00064 -Svcs b/c condition expected last>=12 mos........................................................ 128C00065 -Limited/prevented in ability.............................................................................. 128

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C00066 -Limited b/c medical, behavioral, other............................................................... 128C00067 -Limited b/c condition expected last>=1yr.......................................................... 129C00068 -Get special therapy......................................................................................... 129C00069 -Therapy b/c medical, behavioral, other............................................................. 129C00070 -Therapy b/c condition expected last>=1yr......................................................... 129C00071 -Problem for which gets trtmnt/counseling.......................................................... 130C00072 -Trtmnt/counseling b/c conditn last>=1yr............................................................ 130C00073 -Last time routine preventive care appt.............................................................. 130C00074 -Childs age now.............................................................................................. 130C00075 -Child recd all immunizations............................................................................ 131C00076A -# times child recd Dtap,DT,DTP....................................................................... 131C00076B -# times child recd MMR................................................................................... 131C00076C -# times child recd IPV or OPV......................................................................... 132C00076D -# times child recd Hib...................................................................................... 132C00076E -# times child recd HepB.................................................................................. 133C00076F -# times child recd Varicella.............................................................................. 133C00077A -Talk about growth/development....................................................................... 133C00077B -Talk about behaviors to expect........................................................................ 134C00077C -Talk about dress/bathe/feed child..................................................................... 134C00077D -Talk about help child grow/learn....................................................................... 134C00077E -Talk about tlking/reading/plying w/child............................................................. 134C00077F -Talk about keep child from injured.................................................................... 135C00077G -Talk about make house safe............................................................................ 135C00077H -Talk about make car safe................................................................................ 135C00078 -Is child male or female.................................................................................... 135C00079 -Is child Hispanic/Latino.................................................................................... 136C00080A -Child race:white.............................................................................................. 136C00080B -Child race:Black............................................................................................. 136C00080C -Child race:Asian............................................................................................. 136C00080D -Child race:Native Hawaiian/Pacific Islnd........................................................... 136C00080E -Child race:Am. Indian/Alaskan......................................................................... 137C00081 -Your age now................................................................................................. 137C00082 -Are you male or female................................................................................... 137C00083 -highest grade/level you completed................................................................... 138C00084 -How related to child........................................................................................ 138

NRC SURVEY FIELDING VARIABLES

FLAG_FIN -Final Disposition............................................................................................. 138DUPFLAG -Multiple Response Indicator............................................................................. 138

CODING SCHEME FLAG AND COUNTS

N2 -Coding Scheme Note 2................................................................................... 139N3 -Coding Scheme Note 3................................................................................... 139N4 -Coding Scheme Note 4................................................................................... 139N5 -Coding Scheme Note 5................................................................................... 139N6 -Coding Scheme Note 6................................................................................... 140N7 -Coding Scheme Note 7................................................................................... 140N8 -Coding scheme Note 8................................................................................... 140N9 -Coding scheme Note 9................................................................................... 140N10 -Coding Scheme Note 10................................................................................. 141N11 -Coding Scheme Note 11................................................................................. 141N12 -Coding Scheme Note 12................................................................................. 141N13 -Coding Scheme Note 13................................................................................. 142N14 -Coding Scheme Note 14................................................................................. 142N15 -Coding Scheme Note 15................................................................................. 142N16 -Coding Scheme Note 16................................................................................. 143N17 -Coding Scheme Note 17................................................................................. 143N18 -Coding Scheme Note 18................................................................................. 143

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N19 -Coding Scheme Note 19................................................................................. 144N20 -Coding Scheme Note 20................................................................................. 144N21 -Coding Scheme Note 21................................................................................. 144N22 -Coding Scheme Note 22................................................................................. 145N23 -Coding Scheme Note 23................................................................................. 145N24 -Coding Scheme Note 24................................................................................. 145N25 -Coding Scheme Note 25................................................................................. 146N26 -Coding Scheme Note 26................................................................................. 146N27 -Coding Scheme Note 27................................................................................. 146N28 -Coding Scheme Note 28................................................................................. 147N29 -Coding Scheme Note 29................................................................................. 147N30 -Coding Scheme Note 30................................................................................. 147MISS_1 -Count of: Violates Skip Pattern........................................................................ 147MISS_4 -Count of: Incomplete grid error......................................................................... 148MISS_5 -Count of: Dont know or not sure....................................................................... 148MISS_6 -Count of: Not applicable - valid skip.................................................................. 149MISS_7 -Count of: Out-of-range error............................................................................ 150MISS_8 -Count of: Multiple response error..................................................................... 150MISS_9 -Count of: No response - invalid skip................................................................. 151MISS_TOT -Total number of missing responses.................................................................. 152CONUS -CONUS - CONUS/OCONUS Indicator............................................................. 153XENRLLMT -Enrollment in TRICARE Prime......................................................................... 153XENR_PCM -Enrollment by PCM type................................................................................. 153XINS_COV -Insurance Coverage....................................................................................... 153XBNFGRP -Constructed Beneficiary Group........................................................................ 154KMILWAT1 -Wait <4 wks for well patient visit-Mil................................................................. 154KCIVWAT1 -Wait <4 wks for well patient visit-Civ................................................................. 154KMILOFFC -Office wait of 15 min or more-Mil...................................................................... 154KCIVOFFC -Office wait of 15 min or more-Civ..................................................................... 155KBGPRB1 -Big problem getting referrals to spclst............................................................... 155KBGPRB2 -Big problem getting neccessary care................................................................ 155KMILOP -Outpatient visits to Military facility..................................................................... 155KCIVOP -Outpatient visits to Civilian facility..................................................................... 156KCIVINS -Beneficiary covered by civilian insuranc............................................................ 156POP -DEERS population by CELLNAME for weights.................................................. 157

WEIGHTS

BWT -BWT - Basic Sampling Weight......................................................................... 156WRWT -Final Weight................................................................................................... 157WRWT1 -Replicated/JackKnife Weight 1........................................................................ 158WRWT2 -Replicated/JackKnife Weight 2........................................................................ 158WRWT3 -Replicated/JackKnife Weight 3........................................................................ 158WRWT4 -Replicated/JackKnife Weight 4........................................................................ 159WRWT5 -Replicated/JackKnife Weight 5........................................................................ 159WRWT6 -Replicated/JackKnife Weight 6........................................................................ 159WRWT7 -Replicated/JackKnife Weight 7........................................................................ 160WRWT8 -Replicated/JackKnife Weight 8........................................................................ 160WRWT9 -Replicated/JackKnife Weight 9........................................................................ 160WRWT10 -Replicated/JackKnife Weight 10....................................................................... 161WRWT11 -Replicated/JackKnife Weight 11....................................................................... 161WRWT12 -Replicated/JackKnife Weight 12....................................................................... 161WRWT13 -Replicated/JackKnife Weight 13....................................................................... 162WRWT14 -Replicated/JackKnife Weight 14....................................................................... 162WRWT15 -Replicated/JackKnife Weight 15....................................................................... 162WRWT16 -Replicated/JackKnife Weight 16....................................................................... 163WRWT17 -Replicated/JackKnife Weight 17....................................................................... 163WRWT18 -Replicated/JackKnife Weight 18....................................................................... 163WRWT19 -Replicated/JackKnife Weight 19....................................................................... 164

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WRWT20 -Replicated/JackKnife Weight 20....................................................................... 164WRWT21 -Replicated/JackKnife Weight 21....................................................................... 164WRWT22 -Replicated/JackKnife Weight 22....................................................................... 165WRWT23 -Replicated/JackKnife Weight 23....................................................................... 165WRWT24 -Replicated/JackKnife Weight 24....................................................................... 165WRWT25 -Replicated/JackKnife Weight 25....................................................................... 166WRWT26 -Replicated/JackKnife Weight 26....................................................................... 166WRWT27 -Replicated/JackKnife Weight 27....................................................................... 166WRWT28 -Replicated/JackKnife Weight 28....................................................................... 167WRWT29 -Replicated/JackKnife Weight 29....................................................................... 167WRWT30 -Replicated/JackKnife Weight 30....................................................................... 167WRWT31 -Replicated/JackKnife Weight 31....................................................................... 168WRWT32 -Replicated/JackKnife Weight 32....................................................................... 168WRWT33 -Replicated/JackKnife Weight 33....................................................................... 168WRWT34 -Replicated/JackKnife Weight 34....................................................................... 169WRWT35 -Replicated/JackKnife Weight 35....................................................................... 169WRWT36 -Replicated/JackKnife Weight 36....................................................................... 169WRWT37 -Replicated/JackKnife Weight 37....................................................................... 170WRWT38 -Replicated/JackKnife Weight 38....................................................................... 170WRWT39 -Replicated/JackKnife Weight 39....................................................................... 170WRWT40 -Replicated/JackKnife Weight 40....................................................................... 171WRWT41 -Replicated/JackKnife Weight 41....................................................................... 171WRWT42 -Replicated/JackKnife Weight 42....................................................................... 171WRWT43 -Replicated/JackKnife Weight 43....................................................................... 172WRWT44 -Replicated/JackKnife Weight 44....................................................................... 172WRWT45 -Replicated/JackKnife Weight 45....................................................................... 172WRWT46 -Replicated/JackKnife Weight 46....................................................................... 173WRWT47 -Replicated/JackKnife Weight 47....................................................................... 173WRWT48 -Replicated/JackKnife Weight 48....................................................................... 173WRWT49 -Replicated/JackKnife Weight 49....................................................................... 174WRWT50 -Replicated/JackKnife Weight 50....................................................................... 174WRWT51 -Replicated/JackKnife Weight 51....................................................................... 174WRWT52 -Replicated/JackKnife Weight 52....................................................................... 175WRWT53 -Replicated/JackKnife Weight 53....................................................................... 175WRWT54 -Replicated/JackKnife Weight 54....................................................................... 175WRWT55 -Replicated/JackKnife Weight 55....................................................................... 176WRWT56 -Replicated/JackKnife Weight 56....................................................................... 176WRWT57 -Replicated/JackKnife Weight 57....................................................................... 176WRWT58 -Replicated/JackKnife Weight 58....................................................................... 177WRWT59 -Replicated/JackKnife Weight 59....................................................................... 177WRWT60 -Replicated/JackKnife Weight 60....................................................................... 177

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05/18/23 X


Alphabetical Table of Variables

Page

AGESMPL -AGESMPL - Age............................................................................................ 90BGCSMPL -BGCSMPL - Beneficiary Group....................................................................... 90BWT -BWT - Basic Sampling Weight......................................................................... 156C00001 -Are you adult responsible for child.................................................................... 107C00002 -Which hlth plan did you use most..................................................................... 107C00003 -In last 12 mos,# mos in a row cvrd w/Pln.......................................................... 107C00004A -Child covered by TRICARE Prime................................................................... 108C00004B -Child covered by TRICARE Extra/Standard...................................................... 108C00004C -Child covered by Fed. EMP Health Benefit....................................................... 108C00004D -Child covered by Medicaid............................................................................... 108C00004E -Child covered by Civilian HMO......................................................................... 108C00004F -Child covered by Other Civilian Ins................................................................... 109C00004G -Child covered by USFP................................................................................... 109C00004H -Not sure who Child covered by........................................................................ 109C00004I -Child did not use health plan last 12mos........................................................... 109C00005 -Does child have personal Dr/Nurse.................................................................. 109C00006 -How much prblem to get personal Dr/Nurse...................................................... 110C00007 -Talk about feeling/growing/behaving................................................................. 110C00008 -Rating of childs personal Dr/Nurse................................................................... 110C00009 -Does child have primary care manager............................................................. 111C00010 -Know name of childs Primary care mgr............................................................ 111C00011 -In last 12 mos how much prblm to see PCM..................................................... 111C00012 -Is primary care mgr military or civilian............................................................... 112C00013 -Did you think child needed to see spclst............................................................ 112C00014 -How much prblm to get referral to spclst........................................................... 112C00015 -In last 12 mos did child see specialist............................................................... 112C00016 -Rating of specialist seen most often................................................................. 113C00017 -Specialist same as personal Dr........................................................................ 113C00018 -Call during reg. Hrs to get help/advice.............................................................. 113C00019 -Called during reg Hrs did you get hlp................................................................ 114C00020 -Make appt for regular/routine hlthcre................................................................ 114C00021 -How oftn get appt for care soon as wnted......................................................... 114C00022 -Wait btwn mking appt and seeing provider........................................................ 115C00023 -Have illness/injury need care right away........................................................... 115C00024 -Get needed care as soon as wanted................................................................ 115C00025 -Wait btwn trying to & seeing provider................................................................ 116C00026 -Appointment for well-patient care..................................................................... 116C00027 -Get appt for well-patient care........................................................................... 116C00028 -Wait to see provider for well-patnt care............................................................. 117C00029 -Times to ER................................................................................................... 117C00030 -Times to Dr office/Clinic (excluding ER)............................................................ 117C00031 -Problem to get necessary care........................................................................ 118C00032 -Problem wait for approval................................................................................ 118C00033 -How oftn wait >15 mins................................................................................... 118C00034 -How oftn staff treat w/courtesy &respect........................................................... 119C00035 -How oftn were staff helpful.............................................................................. 119C00036 -How oftn did staff listen carefully...................................................................... 119C00037 -How oftn did staff explain things to you............................................................. 120C00038 -How oftn staff respect what had to say............................................................. 120C00039 -Child old enough to talk to Dr........................................................................... 120

05/18/23 XI


C00040 -Dr explain in way for child to undrstnd............................................................... 121C00041 -How oftn spend enough time w/child................................................................ 121C00042 -Rating of childs healthcare.............................................................................. 122C00043 -Type of facility child used most often................................................................ 122C00044 -Send in any claims......................................................................................... 122C00045 -Handle claim in reasonable time...................................................................... 123C00046 -Handle claim correctly..................................................................................... 123C00047 -Plan make clear how much to pay.................................................................... 123C00048 -Look for info/written material............................................................................ 124C00049 -Find/understand info in written material............................................................. 124C00050 -Call customer service to get info...................................................................... 124C00051 -Problem get help when call customer svc......................................................... 124C00052 -Called/written plan with complaint..................................................................... 125C00053 -How long to resolve complaint......................................................................... 125C00054 -Complaint/problem settled to satisfction............................................................ 125C00055 -Experience with paperwork.............................................................................. 125C00056 -Problem with paperwork.................................................................................. 126C00057 -Rating of exprience with child hlth plan............................................................. 126C00058 -Rate child overall health.................................................................................. 126C00059 -Child use medicine prescribed by Dr................................................................ 127C00060 -Medicine b/c medical,behavioral,other.............................................................. 127C00061 -Medicine b/c cndtn expected last>=12 mos....................................................... 127C00062 -Mre medical,mntl,edcution svcs thn usual......................................................... 127C00063 -Use svcs b/c medical, behavioral, oth............................................................... 128C00064 -Svcs b/c condition expected last>=12 mos........................................................ 128C00065 -Limited/prevented in ability.............................................................................. 128C00066 -Limited b/c medical, behavioral, other............................................................... 128C00067 -Limited b/c condition expected last>=1yr.......................................................... 129C00068 -Get special therapy......................................................................................... 129C00069 -Therapy b/c medical, behavioral, other............................................................. 129C00070 -Therapy b/c condition expected last>=1yr......................................................... 129C00071 -Problem for which gets trtmnt/counseling.......................................................... 130C00072 -Trtmnt/counseling b/c conditn last>=1yr............................................................ 130C00073 -Last time routine preventive care appt.............................................................. 130C00074 -Childs age now.............................................................................................. 130C00075 -Child recd all immunizations............................................................................ 131C00076A -# times child recd Dtap,DT,DTP....................................................................... 131C00076B -# times child recd MMR................................................................................... 131C00076C -# times child recd IPV or OPV......................................................................... 132C00076D -# times child recd Hib...................................................................................... 132C00076E -# times child recd HepB.................................................................................. 133C00076F -# times child recd Varicella.............................................................................. 133C00077A -Talk about growth/development....................................................................... 133C00077B -Talk about behaviors to expect........................................................................ 134C00077C -Talk about dress/bathe/feed child..................................................................... 134C00077D -Talk about help child grow/learn....................................................................... 134C00077E -Talk about tlking/reading/plying w/child............................................................. 134C00077F -Talk about keep child from injured.................................................................... 135C00077G -Talk about make house safe............................................................................ 135C00077H -Talk about make car safe................................................................................ 135C00078 -Is child male or female.................................................................................... 135C00079 -Is child Hispanic/Latino.................................................................................... 136C00080A -Child race:white.............................................................................................. 136C00080B -Child race:Black............................................................................................. 136C00080C -Child race:Asian............................................................................................. 136C00080D -Child race:Native Hawaiian/Pacific Islnd........................................................... 136C00080E -Child race:Am. Indian/Alaskan......................................................................... 137

05/18/23 XII


C00081 -Your age now................................................................................................. 137C00082 -Are you male or female................................................................................... 137C00083 -highest grade/level you completed................................................................... 138C00084 -How related to child........................................................................................ 138CONUS -CONUS - CONUS/OCONUS Indicator............................................................. 153DAGEQY -Age (As of 31 January 2001)........................................................................... 92DBENCAT -Beneficiary Category...................................................................................... 95DCATCH -Catchment Area............................................................................................. 101DMEDELG -Medical Privlege Code.................................................................................... 95DSPONSVC -Derived Sponsor Branch of Service.................................................................. 95DUPFLAG -Multiple Response Indicator............................................................................. 138ENBGSMPL -Enrollment by beneficiary category................................................................... 91ENLSMPL -ENLSMPL - Enrollment Sampling Group.......................................................... 105ENRID -Enrollment DMISID......................................................................................... 96FIELDAGE -Age (As of 1 July 2001)................................................................................... 93FLAG_FIN -Final Disposition............................................................................................. 138FNSTATUS -Final Status.................................................................................................... 105KBGPRB1 -Big problem getting referrals to spclst............................................................... 155KBGPRB2 -Big problem getting neccessary care................................................................ 155KCIVINS -Beneficiary covered by civilian insuranc............................................................ 156KCIVOFFC -Office wait of 15 min or more-Civ..................................................................... 155KCIVOP -Outpatient visits to Civilian facility..................................................................... 156KCIVWAT1 -Wait <4 wks for well patient visit-Civ................................................................. 154KEYCOUNT -# of Key Questions Answered.......................................................................... 106KMILOFFC -Office wait of 15 min or more-Mil...................................................................... 154KMILOP -Outpatient visits to Military facility..................................................................... 155KMILWAT1 -Wait <4 wks for well patient visit-Mil................................................................. 154LEGDDSCD -DDS Code..................................................................................................... 94MBRRELCD -Member Relationship Code............................................................................. 94MEDTYPE -Medicare Type............................................................................................... 96MISS_1 -Count of: Violates Skip Pattern........................................................................ 147MISS_4 -Count of: Incomplete grid error......................................................................... 148MISS_5 -Count of: Dont know or not sure....................................................................... 148MISS_6 -Count of: Not applicable - valid skip.................................................................. 149MISS_7 -Count of: Out-of-range error............................................................................ 150MISS_8 -Count of: Multiple response error..................................................................... 150MISS_9 -Count of: No response - invalid skip................................................................. 151MISS_TOT -Total number of missing responses.................................................................. 152MPCSMPL -MPCSMPL - Military Personnel Category......................................................... 89MPRID -Unique MPR Identifier..................................................................................... 89MRTLSTAT -Marital Status................................................................................................. 92N2 -Coding Scheme Note 2................................................................................... 139N3 -Coding Scheme Note 3................................................................................... 139N4 -Coding Scheme Note 4................................................................................... 139N5 -Coding Scheme Note 5................................................................................... 139N6 -Coding Scheme Note 6................................................................................... 140N7 -Coding Scheme Note 7................................................................................... 140N8 -Coding scheme Note 8................................................................................... 140N9 -Coding scheme Note 9................................................................................... 140N10 -Coding Scheme Note 10................................................................................. 141N11 -Coding Scheme Note 11................................................................................. 141N12 -Coding Scheme Note 12................................................................................. 141N13 -Coding Scheme Note 13................................................................................. 142N14 -Coding Scheme Note 14................................................................................. 142N15 -Coding Scheme Note 15................................................................................. 142N16 -Coding Scheme Note 16................................................................................. 143N17 -Coding Scheme Note 17................................................................................. 143

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N18 -Coding Scheme Note 18................................................................................. 143N19 -Coding Scheme Note 19................................................................................. 144N20 -Coding Scheme Note 20................................................................................. 144N21 -Coding Scheme Note 21................................................................................. 144N22 -Coding Scheme Note 22................................................................................. 145N23 -Coding Scheme Note 23................................................................................. 145N24 -Coding Scheme Note 24................................................................................. 145N25 -Coding Scheme Note 25................................................................................. 146N26 -Coding Scheme Note 26................................................................................. 146N27 -Coding Scheme Note 27................................................................................. 146N28 -Coding Scheme Note 28................................................................................. 147N29 -Coding Scheme Note 29................................................................................. 147N30 -Coding Scheme Note 30................................................................................. 147PATCAT -Aggregated Beneficiary Category..................................................................... 96PCM -Primary Manager Code (CIV or MIL)................................................................ 93PNLCATCD -Personnel Category Code (Duty Status)........................................................... 94POP -DEERS population by CELLNAME for weights.................................................. 157POSTSTR -Post Stratification Cell..................................................................................... 106RACEETHN -Race/Ethnic Code.......................................................................................... 92REGSMPL -REGSMPL - Region....................................................................................... 90SEXSMPL -SEXSMPL - Sex............................................................................................ 89STRATUM -Sampling STRATUM...................................................................................... 91SUPREG -SUPREG - Super Region................................................................................ 92SVCSMPL -SVCSMPL - Branch of Service........................................................................ 89TSPSITE -TSP Site (regardless of age)........................................................................... 93ULOCDMIS -Unit DMISID.................................................................................................. 103WRWT -Final Weight................................................................................................... 157WRWT1 -Replicated/JackKnife Weight 1........................................................................ 158WRWT2 -Replicated/JackKnife Weight 2........................................................................ 158WRWT3 -Replicated/JackKnife Weight 3........................................................................ 158WRWT4 -Replicated/JackKnife Weight 4........................................................................ 159WRWT5 -Replicated/JackKnife Weight 5........................................................................ 159WRWT6 -Replicated/JackKnife Weight 6........................................................................ 159WRWT7 -Replicated/JackKnife Weight 7........................................................................ 160WRWT8 -Replicated/JackKnife Weight 8........................................................................ 160WRWT9 -Replicated/JackKnife Weight 9........................................................................ 160WRWT10 -Replicated/JackKnife Weight 10....................................................................... 161WRWT11 -Replicated/JackKnife Weight 11....................................................................... 161WRWT12 -Replicated/JackKnife Weight 12....................................................................... 161WRWT13 -Replicated/JackKnife Weight 13....................................................................... 162WRWT14 -Replicated/JackKnife Weight 14....................................................................... 162WRWT15 -Replicated/JackKnife Weight 15....................................................................... 162WRWT16 -Replicated/JackKnife Weight 16....................................................................... 163WRWT17 -Replicated/JackKnife Weight 17....................................................................... 163WRWT18 -Replicated/JackKnife Weight 18....................................................................... 163WRWT19 -Replicated/JackKnife Weight 19....................................................................... 164WRWT20 -Replicated/JackKnife Weight 20....................................................................... 164WRWT21 -Replicated/JackKnife Weight 21....................................................................... 164WRWT22 -Replicated/JackKnife Weight 22....................................................................... 165WRWT23 -Replicated/JackKnife Weight 23....................................................................... 165WRWT24 -Replicated/JackKnife Weight 24....................................................................... 165WRWT25 -Replicated/JackKnife Weight 25....................................................................... 166WRWT26 -Replicated/JackKnife Weight 26....................................................................... 166WRWT27 -Replicated/JackKnife Weight 27....................................................................... 166WRWT28 -Replicated/JackKnife Weight 28....................................................................... 167WRWT29 -Replicated/JackKnife Weight 29....................................................................... 167WRWT30 -Replicated/JackKnife Weight 30....................................................................... 167

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WRWT31 -Replicated/JackKnife Weight 31....................................................................... 168WRWT32 -Replicated/JackKnife Weight 32....................................................................... 168WRWT33 -Replicated/JackKnife Weight 33....................................................................... 168WRWT34 -Replicated/JackKnife Weight 34....................................................................... 169WRWT35 -Replicated/JackKnife Weight 35....................................................................... 169WRWT36 -Replicated/JackKnife Weight 36....................................................................... 169WRWT37 -Replicated/JackKnife Weight 37....................................................................... 170WRWT38 -Replicated/JackKnife Weight 38....................................................................... 170WRWT39 -Replicated/JackKnife Weight 39....................................................................... 170WRWT40 -Replicated/JackKnife Weight 40....................................................................... 171WRWT41 -Replicated/JackKnife Weight 41....................................................................... 171WRWT42 -Replicated/JackKnife Weight 42....................................................................... 171WRWT43 -Replicated/JackKnife Weight 43....................................................................... 172WRWT44 -Replicated/JackKnife Weight 44....................................................................... 172WRWT45 -Replicated/JackKnife Weight 45....................................................................... 172WRWT46 -Replicated/JackKnife Weight 46....................................................................... 173WRWT47 -Replicated/JackKnife Weight 47....................................................................... 173WRWT48 -Replicated/JackKnife Weight 48....................................................................... 173WRWT49 -Replicated/JackKnife Weight 49....................................................................... 174WRWT50 -Replicated/JackKnife Weight 50....................................................................... 174WRWT51 -Replicated/JackKnife Weight 51....................................................................... 174WRWT52 -Replicated/JackKnife Weight 52....................................................................... 175WRWT53 -Replicated/JackKnife Weight 53....................................................................... 175WRWT54 -Replicated/JackKnife Weight 54....................................................................... 175WRWT55 -Replicated/JackKnife Weight 55....................................................................... 176WRWT56 -Replicated/JackKnife Weight 56....................................................................... 176WRWT57 -Replicated/JackKnife Weight 57....................................................................... 176WRWT58 -Replicated/JackKnife Weight 58....................................................................... 177WRWT59 -Replicated/JackKnife Weight 59....................................................................... 177WRWT60 -Replicated/JackKnife Weight 60....................................................................... 177XBNFGRP -Constructed Beneficiary Group........................................................................ 154XENR_PCM -Enrollment by PCM type................................................................................. 153XENRLLMT -Enrollment in TRICARE Prime......................................................................... 153XINS_COV -Insurance Coverage....................................................................................... 153

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05/18/23 XVI


IntroductionThis Codebook and Users’ Guide provides programmers and analysts with a tool to assist them in creating their own cross-tabulations and basic statistical estimates using the 2000 Child Health Care Survey of DoD Beneficiaries (HCSDB). It is intended for users wanting to create tables and to perform analyses other than those in the reports associated with this project.

Any user who wishes to recreate specific tables from the analytic report should also refer to “The 2000 Health Care Survey of DoD Beneficiaries: Child Technical Manual.” That document outlines the procedures required to reproduce the child report cards using HCSDB data.

This chapter explains how to use this guide, reviews the survey, briefly describes the sample design, and concludes with a list of other documents on the HCSDB data that may be useful for policymakers, administrators, or other users.

How to Use This Guide

Chapter 2 describes the database conventions and types of variables in the database. This chapter explains the relationship of the raw survey data to the cleaned and constructed variables preferred for data analyses.

Chapter 3 provides table-making instructions in both SAS and SPSS, presenting the basic computer programming code needed to tabulate the data in SAS and the interactive steps for generating tables in SPSS. Either package may be used. While we assume that most users have some knowledge of computer systems and statistical processing, examples of how to create tables and the resulting output are given to simplify the process of tabulating the data. Because of the complex sample design, users interested in measuring the precision of their results will need to use a statistical package capable of calculating standard errors for stratified surveys, such as SUDAANTM or WesVar PC®. Sample programming code is included to estimate standard errors using methods that are appropriate for the complex sample design.

Chapter 4 is the codebook describing each variable in the database, including a list of all possible values of the variable, weighted and unweighted frequency counts and percent occurrences for each value, and the values’ interpretation or formatting. The codebook helps users assess the availability of certain measures, specify variables of interest, and identify all possible values of a variable. The variables are listed in the order of their position on the data file, where they are grouped according to source as follows:

Sampling variables used to place beneficiaries in appropriate strata

Information from the Defense Enrollment Eligibility Reporting System (DEERS) at the time of sampling

Questionnaire responses: cleaned and recoded

Variables created during the fielding of the survey

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Chapter

1


Coding Scheme flags and missing value counts

Constructed variables for analysis

We also provide an alphabetical quick-reference list to help the user locate each variable after the table of contents.

Users who wish to know more about the technical aspects of the database creation, construction of new variables, or MPR’s report production procedures should refer to “The 2000 Health Care Survey of DoD Beneficiaries: Child Technical Manual,” available from the TRICARE Management Activity Office.

What is the HCSDB?

The HCSDB is an annual health care survey that was first fielded in 1995 for active duty military personnel, retirees, and their adult family members. In 1996 and 1997, the survey was expanded to include topics related to health care of children. In those years, the survey consisted of two separate questionnaires: Form A for adults and Form C for children’s topics. The 1998 HCSDB did not include a child survey. With the 1999 HCSDB, fielding of the child survey was resumed. The survey is sponsored by the Assistant Secretary of Defense (Health Affairs) [OASD (HA)], under authority of the National Defense Authorization Act for Fiscal Year 1993 (P.L. 102-484). The child survey assesses parents’ satisfaction with and access to their child’s health care, TRICARE Prime, communication and customer service related to pediatric care.

The 2000 Child HCSDB was closely modeled on the Consumer Assessment of Health Plans Survey (CAHPS) 2.0 H survey instruments so that findings for children in the MHS could be compared with the results of CAHPS surveys of privately insured children in the civilian sector. Most of the survey questions are identical to the CAHPS questions. CAHPS is a survey program sponsored by the Agency for Health Care Research and Quality (AHRQ), U.S. Department of Health and Human Services, and the Picker Institute. The program is designed to monitor the satisfaction and access of civilian health care plan beneficiaries. A few of the questions are “CAHPS-like” but are modified slightly to better fit the MHS context; some questions are unique to issues related to TRICARE. The annotated child questionnaire appears in Appendix A.

The Child HCSDB covers the following topics:

Health Plan. This section collects data on TRICARE Prime enrollment and the use of supplemental insurance and/or other private insurance by the child in the past 12 months.

Your Child’s Personal Doctor or Nurse. In this section, respondents are asked about their relationship with their child’s personal doctor or nurse. They are asked to rate their child’s personal doctor or nurse on a scale of 0 to 10 where 0 is the worst and 10 is the best. There are additional questions on problems receiving care from a TRICARE primary care manager.

Getting Health Care from a Specialist. This section collects information about the child’s need for and access to care from specialists. Respondents rate the specialist that their child sees most frequently on a scale from 0 to 10 where 0 is the worst and 10 is the best.

Calling Doctors’ Offices. In this section, parents are asked about access to care and how frequently they obtain information by telephone.

Your Child’s Health Care in the Last 12 Months. This section collects information on where children of DoD beneficiaries received most of their care in the past 12 months. These are questions on both military and civilian care. This section also contains questions about general and specific care at the facility the child used the most. These questions cover topics such as availability of providers and their staff, convenience, and courtesy and respect shown by providers and their staff. These questions are similar in content and format to questions in CAHPS.

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Your Child’s Health Plan. This section is designed to measure beneficiaries’ satisfaction with their child’s primary health plan. Respondents are asked to rate their child’s health plan on a scale of 0 to 10, where 0 is the worst and 10 is the best. Additionally, respondents are asked questions on problems with claims processing for their child, finding and understanding written materials from their child’s health plan, customer service, processing paperwork, and resolving complaints.

Your Child’s Health. This section collects information about the child’s overall health. Questions regarding the child’s health, any other condition that is limiting, use of medication, use of special therapies, treatment or counseling are included in this section. This section also includes questions about the child’s use of medical, mental health, or educational services or the need for more services.

About Your Child and You. This section collects demographic information about the child, including age, gender, and race. If respondents have children between 1 to 2 years of age, they are asked about the child’s immunization history. Respondents also report their age, gender, education level, and relationship to the child.

Sample Design Overview

The sample of beneficiaries for the child HCSDB was drawn from an extract file of the DEERS database of military health system (MHS) beneficiaries with a reference date of January 31, 2001. The DEERS extract file includes all eligible MHS beneficiaries as follows:

Younger than eighteen years of age on January 31, 2001 and residing only in the United States.

Eligible for military health care benefits as of January 31, 2001.

Sponsor of the child beneficiary must have been a member of one the following: Army, Navy, Air Force, Marine Corps, Coast Guard, Public Health Service (PHS), or National Oceanic and Atmospheric Administration (NOAA).

The sponsor of the child must have been one of the following: active duty, recalled to active duty, academy student/Navy OCS, National Guard, Reserve, transitional loss (RIF), or retired.

A stratified probability sample design was used to select DoD health care beneficiaries for the 2000 Child HCSDB. Strata were defined by a combination of geographic area, age group, and enrollment status. Specific information on the sample design appears in, “The 2000 Health Care Survey of DoD Beneficiaries: Child Sample Report”, Mathematica Policy Research, Washington, D.C.

From a sample of 35,000, 10,762 sponsors of children in MHS completed and returned the 2000 Child HCSDB questionnaire between June 2001 and September 2001, yielding a response rate of 30.8%. Information on developing response rates can be found in “The 2000 Health Care Survey of DoD Beneficiaries: Child Technical Manual”.

Other Documents on the 2000 HCSDB

This document is intended for programmers and analysts using the 2000 Child HCSDB data. Following is a list of other documents that may be requested from the TRICARE Management Activity Office:

The 2000 Health Care Survey of DoD Beneficiaries: Child Sample Design

The 2000 Health Care Survey of DoD Beneficiaries: Child Technical Manual

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05/18/23 4


Description of the Child HCSDB DatabaseThis chapter presents the procedures for developing the database, and presents the database file layout.

Variable Naming Conventions

The conventions used to name variables on the 2000 Child HCSDB data file are listed below and summarized in Tables 2.1.

Survey Variables. Survey variable names consist of up to eight alphanumeric characters that start with an alpha character ("C" for Child survey variables), followed by a year designation ("00") and ending with question number and, if necessary, one alpha character to identify the relevant survey question. For example, the variable representing the first question on the Child survey is given the name C00001. Recoded variables have the same names as on the survey. The original ones are suffixed with “_O” (these will not be on the public release file).

Coding Scheme Flags and Counts. Coding Scheme flags, variables N1-30, reference the notes in the Coding Scheme for Child Survey. N2, for example, is set when checking the values of C00005, C00006 through C00008. See the Coding Scheme in Appendix C for more information. Coding Scheme counts are sums of missing value responses for each questionnaire; each of these variable names begins with the 4 characters “MISS”.

Constructed Independent Variables. Independent variables are prefixed with an "X." These include original survey variables modified as a result of data cleaning or recoding and newly constructed variables that did not previously exist on the survey file. For example, since the variable PCM was modified as a result of data cleaning and recoding, it was renamed XENR_PCM.

Constructed Dependent Variables. All newly constructed dependent variables are prefixed with a “K”.

Weighting Variables. Weighting variables are prefixed with a "W."

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Chapter

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TABLE 2.1

NAMING CONVENTIONS FOR 2000 HCSDB VARIABLES(VARIABLES REPRESENTING SURVEY QUESTIONS)

1st Character:Survey Type

2nd – 3rd

Characters:Survey Year

4th – 6th

Characters:Question #

Additional Characters:Additional Information

C= HealthBeneficiaries (17 andyounger, Child Questionnaire)

00 001-084 A to I are used to label responses associated with a multiple response question

(Constructed Variables)

1st Characters:Variable Group

Additional Characters:Additional Information

N=Coding scheme notes Number referring to Note, e.g., N2

X=Constructed independent variable Descriptive text, e.g., XENRLLMT

K=Constructed dependent variables Descriptive text, e.g., KMILOP (Total number of outpatient visits to a military facility)

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Cleaning and Editing Conventions

Data quality procedures are found in the Coding Scheme tables. The complete Coding Scheme appears in Appendix C. It contains detailed instructions for all editing procedures used to correct data inconsistencies and errors. Editing procedures check for appropriate response values and consistent responses throughout the questionnaire. The steps to insure data quality include the following:

Initial Cleaning. Missing value flags were encoded when NRC created the SAS dataset:

- Skipped items were encoded with SAS missing value code of ‘.’.

- Multiple responses, where there should be a single response, were encoded with SAS missing value ‘.A’.

- Incomplete grid responses were encoded as SAS missing value ‘.I’ with two exceptions: 1) If there was a response in the right column(s) and none in the left column(s), the missing grids were zero-filled; 2) if there was a response in the left column(s) and none in the right column(s), the field was right-adjusted and then zero-filled.

Data Cleaning and Recoding of Variables – Implementation of the Coding Scheme. Skip patterns were checked for consistency, and questions that were skipped legitimately were recoded with the SAS missing value of “.N”; questions that were answered, but should have been skipped, were recoded with a SAS missing value of “.C”. When possible, variables were backward coded or forward coded to make all responses consistent within a sequence. Numeric values were checked, and values that were out of range were flagged with the SAS missing value of “.O”.

Frequency Checks. Formatted and unformatted frequency tables for all variables in the 2000 Child HCSDB data file appear in Chapter 4 of this document. These frequency tables and other relevant cross tabulations were used to examine the range of values recorded for each data item to determine the type and magnitude of missing values. All value labels have been checked for accuracy.

Record Selection Criteria

Blank returns, nonrespondents, and any respondents found to be ineligible for MHS benefits were removed from the database. In addition, among eligible respondents with a non-blank questionnaire, a questionnaire must be “complete” to be included in the database.

To determine if a child questionnaire is “complete”, 27 key questions were chosen. At least 50 percent of these key items (fourteen or more) must be answered for a questionnaire . The key questions are: 2, 3, 5, 9, 13, 18, 20, 23, 26, 29, 30, 43, 44, 48, 50, 52, 55, 57, 58, 74, 78, 49, 80, 81, 82, 83, and 84. These key questions were adapted from the complete questionnaire rule developed by AHRQ for CAHPS surveys.

We retained 10,762 eligible respondents.

Weighting Procedures

The analysis of survey data from complex sample designs, such as the 2000 Child HCSDB, requires weights to do the following:

Compensate for variable probabilities of selection

Adjust for differential response rates

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Improve the precision of the survey-based estimates through post-stratification [for details, see Brick and Kalton (1996) and references cited therein]

Sampling weights are equivalent to the reciprocal of the probability of each respondent’s selection into the sample. Sampling weights are further adjusted for nonresponse within classes defined by sampling strata: a cross-classification of enrollment status, geographic area, and beneficiary group. These nonresponse-adjusted weights are then ratio-adjusted to population counts from the DEERS files to compensate for variations from the estimated population counts. To properly weigh the data, an analyst should use the final weight WRWT Chapter 4 contains weighted and unweighted frequencies for each variable included in this data set.

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Programming GuideThis chapter is designed to help users create tables and variance estimates. Procedures for using SAS, SPSS, SUDAAN, and WesVarPC to create estimates are explained. Examples provided in the text are based on a preliminary version of the 2000 child data.

How To Make a Table Using SAS

The 2000 Child HCSDB dataset is provided in a Statistical Analysis System (SAS) format. SAS is a computer software system used for data management, summarization, and analysis. A format library for the child database is included along with the dataset. SAS can be run interactively or non-interactively (in batch mode), and the sample programs presented here can be run using either method. Special instructions are given later in the chapter for working interactively with the SAS Display Manager System in a Windows environment. All SAS programs generate a LOG and a LST file. The LOG file shows how SAS interprets your program and flags SAS syntax errors. The LST file shows the requested output.

File References, Libraries, and Options

SAS recognizes two types of datasets -- permanent and temporary. Permanent datasets, such as the HCSDB, are located through a LIBNAME that references the directory where the data is stored. For example, if the child dataset for 2000 is located on a CD-ROM in the subdirectory HCSDB99\FORMC, your LIBNAME statement must look like this:

LIBNAME INFORMC 'F:\HCSDB99\FORMC’;

The Form C dataset can then be referred to as INFORMC.HCSDB99C, where INFORMC is the location of the file HCSDB99C.

A format library requires a LIBNAME LIBRARY statement that shows the location of the format library. For example, if the Form C format library is stored on your hard drive in a FMTLIB subdirectory, the LIBNAME statement should look like this:

LIBNAME LIBRARY 'C:\HCSDB99\FORMC\FMTLIB';

The OPTIONS statement controls page format and line length. A table with a “portrait” orientation might have this statement:

OPTIONS PS=79 LS=132;

A table with a “landscape” orientation that is left justified would have this OPTIONS statement:

OPTIONS PS=50 LS=175 NOCENTER;

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Chapter

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DATA Step

The DATA step is used to create permanent or temporary datasets. It is also used to create new variables, modify existing variables, and limit the number of variables or observations. In a DATA step, you can do any or all of the following activities:

Construct new variables. For example, to construct a variable of family of active duty by sex:

/* Family of Active duty males */IF SEXSMPL = 1 AND BGCSMPL = 2 THEN XSEX_AD = 1; * Family of Active duty females;ELSE IF SEXSMPL = 2 and BGCSMPL = 2 THEN XSEX_AD = 2;ELSE XSEX_AD = .; /* missing value */

[Note: the two methods to insert comments: enclosed within /* */ or beginning with * and ending with a semicolon]

Modify existing variables. For example, if the respondent is in super region 2, the respondent will be placed in the combined super region 2/3:

IF SUPREG = 2 THEN SUPREG = 3

Limit the number of variables. Use a KEEP statement:

KEEP SUPREG REGSMPL C00057 C00058;

Limit the number of observations. Use a subsetting IF:

/* Keep only super region 3 observations */IF SUPREG = 3;

Create a new temporary dataset. For example, CAC_1 is a temporary file of observations for only those respondents in region 1:

LIBNAME INFORMC 'F:\HCSDB00\FORMC';DATA CAC_1;/* Input file is HCSDB00C */SET INFORMC.HCSDB00C;IF REGSMPL = 1;RUN;

Create a new permanent dataset. For example, OUT.CAC_2000 is a permanent dataset only of Region 2 respondents:

LIBNAME INFORMC 'F:\HCSDB00\FORMC';LIBNAME OUT 'C:\HCSDB00\FORMC';DATA OUT.CAC_2000;SET INFORMC.HCSDB00C;IF REGSMPL = 2;RUN;

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PROC TABULATE

PROC TABULATE produces summary statistics in a table layout. The table can have up to three dimensions: page, row, and column. Within any dimension, multiple variables can be reported one after another or hierarchically. Useful statistics that are available in PROC TABULATE include:

N number of observations with nonmissing values

NMISS number of observations with missing values

MEAN the arithmetic mean

SUM the sum

PCTN percent that one frequency represents of another frequency

PCTSUM percent that one sum represents of another sum

The essential elements to execute PROC TABULATE are outlined below (items within < > are not required):

PROC TABULATE DATA=your dataset <option list>;CLASS class variables;VAR analysis variables;TABLE << page expression, > row expression, > column expression </ table

options >;WEIGHT WRWT;RUN;

If the input file is to be limited to a specific population, a separate DATA step can precede the TABULATE, or a WHERE statement can be used within the TABULATE procedure. For example, to create a table from only respondents in Region 1, you would use the following statement after the PROC TABULATE statement:

WHERE REGSMPL = 1;

CLASS variables are any variables that are used for grouping; variables such as SUPREG, SEXSMPL, and REGSMPL are good examples of class variables. Class variables can be either character or numeric and typically have a discrete number of values. Unless MISSING is specified in the options list in the PROC TABULATE state, any observations with a missing CLASS variable will be dropped from the table.

The VAR statement identifies all analysis variables for a table. Analysis variables must be numeric and can be either discrete or continuous. SAS excludes missing values when computing statistics such as means and percentages.

The WEIGHT statement identifies the numeric variable whose value is used for weighting each analysis variable. In the HCSDB for 2000, the weight variable is WRWT.

The TABLE statement defines the table features. Every variable listed in this statement must be classified as either a class variable or an analysis variable in the CLASS or VAR statements. A comma separates each table dimension (page, row, and column). If there are three dimensions, the first is the page, the second is the row, and the last is the column. If there are only two dimensions, the first is the row and the second is the column. Tables with only one dimension are in column form. Each dimension expression is composed of the same following elements:

Analysis variables

Class variables

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The universal class variable ALL, which summarizes the class variables in the same group or dimension

Keyword for the statistic to be performed, such as MEAN, SUM, or PCTSUM

A format modifier, which defines how to format values in cells. For example, F=8.2 will present values with a maximum of 8 positions and 2 digits to the right of the decimal.

Labels, which temporarily replace variable names and statistic keywords. These labels have the form ='label'; for example, REGSMPL='Region' or MEAN=' ' (to eliminate the word MEAN from the headings).

Crossing operator * (asterisk). The asterisk is used to cross elements within the same dimension. For example, you would use XENRLLMT*SEXSMPL to cross enrollment status by sex. The asterisk is also used to connect the statistic (e.g., MEAN, SUM) to the appropriate dimension; for example, to calculate the mean of respondents’ satisfaction with all their children’s health care in the last 12 months, you would use c00057 *MEAN.

Denominator definitions are enclosed by < > (brackets).

Concatenation operator is a single space between elements in a dimension. For example, to concatenate satisfaction with all their children’s health care in the last 12 months with satisfaction with their children’s health plan, you would use C00057 C00042.

Grouping is accomplished with parentheses. Below is an example of grouping, concatenation, and crossing within a single dimension:

(BGCSMPL ALL)*SEXSMPL

The SAS Display Manager System

The SAS Display Manager system provides an interactive tool for running SAS commands, like those given above, in the Windows environment. Double clicking the SAS icon on the desktop begins the SAS session. When you first enter the system, the following screen opens.

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The screen is divided into three windows, each corresponding to an aspect of your SAS session. The Program Editor is the window where you compose, edit, and run your SAS commands. The Log window displays messages from the SAS system as well as your SAS statements as they are executed. Any error messages appear in the Log. The Output window displays the output tables requested in procedure commands written in the Program Editor. Toggling among the windows is accomplished by clicking anywhere in a given window. The cursor will jump to the selected window. Below are some options for customizing these screens by defining Preferences.

Clicking on Options results in the following screen.

Click on Preferences as highlighted above, and the following screen will open.

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Many of these settings are system default options. To add a command line to the three windows, you would click in the box opposite Command Line, causing a check mark to appear in the box. Your screen should resemble the screen above. Click on Save and the screen will change to the following.

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Each window shows the word Command followed by an arrow. Commands may be typed at this location. To arrive at the command line, depress the Home button on your keyboard. The cursor will appear opposite the arrow.

Toggling among the windows may be accomplished by typing the desired window name at the command line and pressing Enter. SAS recognizes Pgm as the abbreviated reference to the Program Editor and Out as a shortened name for the Output window. A few keystrokes allow you to navigate among the windows. For example, the command line lets you continue to customize our SAS session as follows.

In order to more easily distinguish between the SAS windows, it may be preferable to change the background color of selected windows. As an example, set the background color of the Log window to pink and the Output window to gray. Press the Home key to arrive at the command line. Type Log opposite the arrow to toggle to the Log window. Type the command, color back pink (or some other color) on the command line. Your screen will resemble the following.

Press Enter to process the commands and the window will shade to pink. Toggle to the Output window by typing Out and keying Enter. Type color back gray and key Enter. These changes make it easier to distinguish between the windows at a glance. The screen looks like the following.

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The following option also uses color to distinguish between windows.

All SAS statements for building and processing SAS datasets are typed into the Program editor. A SAS session may involve typing statements like the ones above for library reference, computing new variables, data steps, etc. Entering a long series of statements in such a small space may be awkward, so another arrangement for the windows may be preferable.

Cascading the windows is one option. To cascade the windows, open the Window menu, and choose Cascade as indicated in the following.

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Clicking the option Cascade produces the following result.

Each window is partly superimposed on the other. The colors distinguish between windows at a glance. With the Program Editor in front, SAS statements may be typed there with relative ease.

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As a final option, you can enlarge the Program Editor to fill the entire screen. At the command line, type zoom as in the following:

The window changes to fill the screen.

One more option for customizing screens is explained below. This involves adding line numbers to the editing environment in the Program Window. After adding the line numbers, many useful line-editing commands become available (see the SAS Manual). On the Edit menu choose Options and Numbers as in the following screen.

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The line numbers appear at the left of the full screen Program Editor as in the screen below, and the SAS statements can be typed into the screen and edited.

Below is an example of a PROC TABULATE to construct a table of health care variables by beneficiary group by gender for respondents in region 3. Beneficiary group (BGCSMPL) and sex

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(SEX) are both class variables with a discrete number of values. The columns of the table are beneficiary group broken out by sex, a total for each beneficiary group, and a region total. The health care variables (C00057 and C00058) are the analysis variables appearing as the rows of the table. The statistic that we want to see is the weighted mean of these variables for each group in the table and for the entire region as a whole.

Enter the following SAS statements into the Program Editor.

OPTIONS PS=79 LS=95;LIBNAME IN ‘J:\DOD\Q3_2000\DATA\CFINAL’;LIBNAME LIBRARY ‘J:\DOD\Q3_2000\DATA\CFINAL\FMTLIB’;PROC TABULATE DATA=IN.HCS00C_1;WHERE SUPREG = 1; /* limit to Region 1 */CLASS BGCSMPL SEXSMPL;VAR C00057 C00058;WEIGHT WRWT99;TABLE (C00057 C00058)*MEAN, /* Row Dimension */

BGCSMPL*(SEXSMPL ALL) ALL; /* Column Dimension */TITLE “Table III-1”;TITLE2’ Beneficiary Group by Gender for SUPER REGION 1';RUN;

Key Home and type the command SUBMIT on the Command Line. Submit instructs the SAS system to process the commands written in the Program Editor. Your screen should resemble the following.

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Enter the Submit command, and the SAS statements disappear from the Program Editor.If a table is successfully produced, the Output window will open and the table will be displayed. If no output is produced, then SAS has encountered an error. SAS statements about the error can be seen and evaluated in the Log window. In all cases, the Log window should be carefully examined after SAS statements are processed. SAS may produce a table even if there are errors in the program, so the table may not be correct.

No table was produced for this run. The error is indicated in the Log Window as shown below.

The variable WRWT99 was not found in the dataset. Type Pgm on the Command line to return to the Program Editor. Type Recall on the Command line and the program statements will reappear in the window.

You can correct the error by entering the correct variable name, WRWT into the program and rerunning the procedure.

The corrected program produces the following output.

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The result of this process is Table III.1.

Note that the TITLE statement defines the heading for each page. Titles of more than one line are entered as TITLE, TITLE2, etc.

Table III.1Beneficiary Group by Gender for Super Region 1

--------------------------------------------------------------------------------------- | | BGCSMPL - Beneficiary Group | | |----------------------------------------------------------------| | | Active Duty | | | |-------------------------| Family of Active | | | SEXSMPL - | |--------------------------------------| | | Sex | | SEXSMPL - Sex | | | |------------| |-------------------------| | | | Male | All | Male | Female | All | |---------+----------+------------+------------+------------+------------+------------| |Rating of|Mean | | | | | | |exprience| | | | | | | |with | | | | | | | |child | | | | | | | |hlth plan| | 9.00| 9.00| 6.66| 6.84| 6.75| |---------+----------+------------+------------+------------+------------+------------| |Rate |Mean | | | | | | |child | | | | | | | |overall | | | | | | | |health | | 4.00| 4.00| 4.35| 4.40| 4.37| ---------------------------------------------------------------------------------------

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(CONTINUED) Table III.1 Beneficiary Group by Gender for Super Region 1

-------------------------------------------------------------------------- | | BGCSMPL - Beneficiary Group | | | |--------------------------------------| | | | Ret/Surv/Fam <65 | | | |--------------------------------------| | | | SEXSMPL - Sex | | | | |-------------------------| | | | | Male | Female | All | All | |--------------------+------------+------------+------------+------------| |Rating of|Mean | | | | | |exprience| | | | | | |with | | | | | | |child | | | | | | |hlth plan| | 7.08| 7.28| 7.17| 6.91| |---------+----------+------------+------------+------------+------------| |Rate |Mean | | | | | |child | | | | | | |overall | | | | | | |health | | 4.26| 4.34| 4.30| 4.34| --------------------------------------------------------------------------

Using FormatsThe format library is the key to interpreting values of discrete variables. For example, in the program above, the format library found at J:\DOD\Q3_2000\CFINAL\FMTLIB indicates that a Value of 1 for SEXSMPL means male, and a value of 2 for SEXSMPL means female. Similarly, if BGCSMPL equals 2, the respondent is a family member of active duty personnel; if BGCSMPL equals 3, the respondent is an under-65 retiree or a survivor or one of their family members.

Since formats are associated with the variables in the HCSDB, formatting is automatic as long as SAS can locate the format library. Error messages will result if the LIBNAME LIBRARY statement is not present. If the format library is not available for some reason, use the statement

FORMAT _ALL_;

within the PROC TABULATE to prevent SAS from searching for the missing format library. The default formats in the format library were used to produce the table described in the previous section.

Table AppearanceFormat modifiers and temporary labels improve the appearance of a table. In Table III.1, the values of the statistics are of the form x.xx. If each cell is defined to be six positions wide with two positions to the right of the decimal, there is adequate space plus some extra room to keep the table from looking crowded. This is done by crossing the statistic with the format modifier:

MEAN*F=6.2

Labels are attached to all variables in the HCSDB. You can use temporary labels to override the label within the SAS dataset. It is not always necessary to use both the variable label and the formatted values for each value of a class variable. In the previous example, the formatted values of BGCSMPL are active duty, family members of active duty, etc. which we know to be beneficiary groups; the title also tells you that these are beneficiary groups. The table can be made attractive by deleting the heading for BGCSMPL by including a blank for the temporary label:

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BGCSMPL=’ ‘

Similarly, because the statistic being reported here is a mean, you do not need MEAN on each row. You can add or eliminate a label and include a format modifier to the same variable:

MEAN=’ ‘*F=6.2

The headings for SEX and ALL can be improved:

SEXSMPL=’Gender’ALL=’Group Total’ for the ALL that is crossed with BGCSMPLALL=’Total’ for the Region 3 total

The new program looks like this:

OPTIONS PS=79 LS=95;LIBNAME IN 'J:\DOD\Q3_2000\CFINAL';LIBNAME LIBRARY ‘J:\DOD\Q3_2000\CFINAL\FMTLIB’;PROC TABULATE DATA=IN.HCS00C_1;WHERE SUPREG = 1; /* limit to Region 1 */CLASS BGCSMPL SEXSMPL;VAR C00057 C00058;WEIGHT WRWT;TABLE (C00057 C00058)*MEAN=’ ‘*F=6.2, /* Row Dimension */

/* Column Dimension */BGCSMPL=’ ‘*(SEXSMPL=’Gender’ ALL=’Group Total’) ALL=’Total’;

TITLE “Table III.2”;TITLE2 ‘Beneficiary Group by Gender for SUPER REGION 1';RUN;Typing these statements into the Program Window produces the following screen.

After the Submit command is entered, the following table is displayed in the Output window.

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The resulting output is in Table III.2.

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------------------------------------------------------------------------------------- | | Active Duty | Family of Active | Ret/Surv/Fam <65 | | | |-------------+--------------------+--------------------| | | |Gender| | Gender | | Gender | | | | |------|Group |-------------|Group |-------------|Group | | | | Male |Total | Male |Female|Total | Male |Female|Total |Total | |--------------------+------+------+------+------+------+------+------+------+------| |Rating of| | | | | | | | | | | |exprience| | | | | | | | | | | |with | | | | | | | | | | | |child | | | | | | | | | | | |hlth plan| | 9.00| 9.00| 6.66| 6.84| 6.75| 7.08| 7.28| 7.17| 6.91| |---------+----------+------+------+------+------+------+------+------+------+------| |Rate | | | | | | | | | | | |child | | | | | | | | | | | |overall | | | | | | | | | | | |health | | 4.00| 4.00| 4.35| 4.40| 4.37| 4.26| 4.34| 4.30| 4.34| -------------------------------------------------------------------------------------

Although the label for MEAN is deleted, there is still a space in the table for this label. You can eliminate this blank space by using the TABLE option of ROW=FLOAT. SAS row headings are automatically allocated; you can override this by using the TABLE option of RTS=n where n is an integer value specifying the number of print positions to be used for row headings. If you decide that we don’t need the label ‘Gender’ for SEXSMPL because ‘male’ and ‘female’ are self-explanatory, the revised program is as follows:

OPTIONS PS=79 LS=95;LIBNAME IN 'J:\DOD\Q3_2000\CFINAL';LIBNAME LIBRARY ‘J:\DOD\Q3_2000\CFINAL\FMTLIB’;PROC TABULATE DATA=IN.HC500C_1;WHERE SUPREG = 1; /* limit to Region 1 */CLASS BGCSMPL SEXSMPL;VAR C00057 C00058;WEIGHT WRWT;TABLE (C00057 C00058)*MEAN=’ ‘*F=6.2, /* Row Dimension *//* Column Dimension */BGCSMPL=’ ‘*(SEXSMPL=’ ’ ALL=’Group Total’) ALL=’Total’ / ROW=FLOAT RTS=32; Title “Table III.3”;

TITLE2’ Beneficiary Group by Gender for SUPER REGION 1';RUN;

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Typed into the Program Window, the revised program appears as follows.

The output table is displayed in the Output Window as follows.

The result is Table III.3.

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----------------------------------------------------------------------------------------| | Active Duty | Family of Active | Ret/Surv/Fam <65 || |-------------+--------------------+--------------------|| | |Group | | |Group | | |Group || | Male |Total | Male |Female|Total | Male |Female|Total ||------------------------------+------+------+------+------+------+------+------+------||Rating of exprience with child| | | | | | | | ||hlth plan | 9.00| 9.00| 6.66| 6.84| 6.75| 7.08| 7.28| 7.17||------------------------------+------+------+------+------+------+------+------+------||Rate child overall health | 4.00| 4.00| 4.35| 4.40| 4.37| 4.26| 4.34| 4.30|----------------------------------------------------------------------------------------

(CONTINUED) --------------------------------------- | |Total | |------------------------------+------| |Rating of exprience with child| | |hlth plan | 6.91| |------------------------------+------| |Rate child overall health | 4.34| ---------------------------------------

Calculating PercentsWhen calculating percentages, it is necessary to appropriately define the denominator. To calculate a column percentage, the denominator definition must include all class variables that define the row. For example, if you want to look at the percentage of people in your region and each of the catchment areas who answered yes (or no) to question 15, ‘In the last 12 months, did your child see a specialist?', your TABLE statement in the TABULATE procedure would look like this:

WHERE SUPREG = 2;

TABLE C00015 ALL=’Total’,

(All=’Region Total’ REGSMPL)*PCTN<C00015 ALL>=’Percent’;

Table III.4 includes a program and its output for calculating column percentages.

The program statements in the Program Editor appear as follows.

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The submitted statements produce the following output.

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Table III.4 Children Who Saw a Specialist in the Last 12 Months for Super Region 2 Regions

------------------------------------------------------------------------------------------| | | | Southern | | || |Region Total| Southwest | California |Golden Gate | Northwest || |------------+------------+------------+------------+------------|| | # | % | # | % | # | % | # | % | # | % ||-----------------------+-----+------+-----+------+-----+------+-----+------+-----+------||In last 12 mos did | | | | | | | | | | ||child see specialist | | | | | | | | | | ||-----------------------| | | | | | | | | | ||Yes | 871| 85.73| 377| 86.27| 202| 85.23| 82| 83.67| 133| 85.81||-----------------------+-----+------+-----+------+-----+------+-----+------+-----+------||No | 145| 14.27| 60| 13.73| 35| 14.77| 16| 16.33| 22| 14.19||-----------------------+-----+------+-----+------+-----+------+-----+------+-----+------||Total | 1016|100.00| 437|100.00| 237|100.00| 98|100.00| 155|100.00|------------------------------------------------------------------------------------------(CONTINUED)

--------------------------------------------------- | | Hawaii | Alaska | | |------------+------------| | | # | % | # | % | |-----------------------+-----+------+-----+------| |In last 12 mos did | | | | | |child see specialist | | | | | |-----------------------+ | | | | |Yes | 60| 90.91| 17| 73.91| |-----------------------+-----+------+-----+------| |No | 6| 9.09| 6| 26.09| |-----------------------+-----+------+-----+------| |Total | 66|100.00| 23|100.00| ---------------------------------------------------

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The statistic N is included with PCTN to make it easier to verify that the denominator definitions have been set up properly. After you check to see that the percentages are accurate, the N statistic can be removed. Note that the output for Table III.4 is unweighted. The N statistic (and PCTN statistic) is always unweighted even if a WEIGHT statement is included.

Similarly, if you want to look at the percentage of TRICARE enrollees (and non-enrollees) by gender who answered yes to question 15, this would be a row percentage. To calculate a row percentage, the denominator definition must include all class variables that define the column. Your TABLE statement would look like this:

TABLE C00015 ALL=’Total’,XENRLLMT *(SEXSMPL=’ ‘ All=’Group Total’)*PCTN<XENRLLMT*SEXSMPL XENRLLMT*ALL>=’Percent’;

Notice that there are no parentheses used in the denominator definition. Because parenthetical groupings are not allowed in the denominator definition, all crossings and concatenations must be included. As noted above, the N and PCTN statistic are unweighted counts of CLASS variables. If you want to produce a weighted count and percentage for this table, you would include WRWT (the 2000 weight variable) as an analysis variable in the VAR statement and in the column crossing of the TABLE statement; the statistics to be generated should be specified as SUM and PCTSUM. A program and output to demonstrate weighted row percentages appears in Table III.5.

The following screen shows the new program typed into the Program Editor.

These commands produce the following output.

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Here, as above, the SUM statistic is included to help determine the accuracy of the denominator definition.

Additional information about running SAS is available from the SAS Institute. Please consult the appropriate manuals for more detailed information.

See Table III.5 to view the entire table.

Table III.5Children Who Saw a Specialist in the Last 12 Months

by TRICARE Prime Enrollment and GenderSuper Region 2 Only

---------------------------------------------------------------------------------------- | | Enrolled | Not enrolled | | |-----------------------------------+-----------------------------------| | | Male | Female |Group Total| Male | Female |Group Total| | |-----------+-----------+-----------+-----------+-----------+-----------| | | # | % | # | % | # | % | # | % | # | % | # | % | |--------------+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----| |In last 12 mos| | | | | | | | | | | | | |did child see | | | | | | | | | | | | | |specialist | | | | | | | | | | | | | |--------------| | | | | | | | | | | | | |Yes |56148|39.20|47561|33.21|104E3|72.41|23099|16.13|16410|11.46|39509|27.59| |--------------+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----| |No | 7740|34.02| 7901|34.73|15640|68.75| 2715|11.93| 4395|19.32| 7109|31.25| |--------------+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----| |Total |63888|38.49|55462|33.42|119E3|71.91|25814|15.55|20804|12.54|46618|28.09| ----------------------------------------------------------------------------------------

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How to Make a Table Using SPSS

The 2000 Child HCSDB dataset is in an SPSS format. SPSS is a computer software system used for data management, summarization, and analysis. SPSS can be run interactively, using menus, or in batch mode, using syntax commands. This guide instructs users on how to use SPSS dialog boxes to:

Construct new variables

Recode existing variables

Select cases for analysis

Weight cases for analysis

Create customized tables

As you use the dialog boxes, you generate syntax automatically. This syntax may be pasted into a syntax file for future use or for modification.

Locating and opening the data file

To begin an SPSS session, double click on the SPSS icon on your desktop. The Data Editor window will open and present a blank spreadsheet like the following screen:

Click on File in the upper left corner to open the following menu:

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Select the Open option or choose a file from the list displayed. Open produces the following screen:

If the file is not in this directory, navigate through your folders until you locate it. Mark the file and click Open. You will be returned to the spreadsheet Data Editor with the file on view. The 2000 Child HCSDB dataset has been opened and is displayed below.

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Constructing new variables

Data can be evaluated from many different aspects. It is sometimes useful to build new variables from combinations of the existing ones and to examine their distributions.

For example, the variable in the file for beneficiary group at the time of sampling is called BGCSMPL, and the variable for sex is SEXSMPL. The value 1 for BGCSMPL indicates that the sponsor is on active duty. The relationships for constructing a new variable for family of active duty by sex are:

Family of active-duty-males: SEXSMPL=1 and BGCSMPL=1

Family of active-duty-females: SEXSMPL=2 and BGCSMPL=1

Open the Transform menu and select Compute as in the following:

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The following dialog box will open:

You can build the new variable in two steps to express the two conditions. The first task is to give the new variable a name and its first value. Enter the Target Variable slot and name the new variable sex_ad. Next, assign the value 1 to sex_ad by entering it into the slot for Numeric Expression. Your screen should look like the following:

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Once you we have assigned the value 1 to sex_ad, you can build the condition that qualifies the assignment. Click on If..and open the following dialog box:

Click on the circle indicating Include if case satisfies condition, and the black dot will move to that circle. The slot underneath will open, ready for your input. Build the “if” condition. Write it directly into the slot or move the elements into the slot from the given options. Add the elements SEXSMPL=1 & BGCSMPL = 1.

The screen should resemble the following:

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Click on Continue and return to the previous screen, which will now look like this:

Your condition will be written next to the If button. Click on OK to exit the dialog box, and the variable sex_ad will be created with its value set to 1.

The next step is to build the second condition for the new variable, which will set it to the value 2. Reopen the Compute dialog box. The commands you just gave still appear in the dialog box. Simply assign the value 2 to sex_ad, press If, and enter ‘f’ for the value of sexsmpl . Click Continue, and finish with OK. The condition, sexsmpl = 2 and bgcsmpl = 1, will be added to the new variable sex_ad.

Once you have created a new variable, you may want to add it permanently to the dataset. The new variable is computed for each case in the file and added to the view in the Data Window after the last variable in the dataset. The variable name is the column heading.

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Since the HCSDB data set carries Read-Only status to protect it from corruption, changes to it cannot be saved. At the end of the day, when the work session ends and you exit SPSS, the file will revert to its former status and the new variables will be lost. The solution is to save the dataset under a new name when you exit. Choose the Save As option on the File menu, and you will be prompted to name the file and to save it in a folder of your choosing. Give the file a new name and save it. Open the new expanded file anytime for processing.

Suppose you do not want to use up your disk space for expanded copies of the dataset. Another option is to save the syntax you have generated in a file that can be run as it is needed. Syntax is a written instruction generated by the commands you give in a dialog box. These “sentences” can be saved in a file and executed when needed. This is the batch mode of processing syntax commands. Syntax files take up very little space.

Experienced SPSS programmers, who have mastered SPSS syntax, often prefer to work only in batch mode. This option is available to users who have not mastered the syntax language. You can paste the commands, generated interactively in the dialog box, onto a syntax file.

Recall the compute example for the new variable sex_ad. The screen below is the result of assigning 1 to sex_ad according to an If condition. You clicked on OK to set the value. Returning to the screen and clicking on Paste writes the command to a syntax file.

Click on the Paste button, and the syntax window below will open with the syntax written in it.

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Now return to the compute dialog box.

Assign the value 2 to sex_ad as in the diagram above. Select Paste, and these commands will be appended to the syntax file.

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The results appear in the screen above. SPSS gives default names to syntax files, such as Syntax1, Syntax2, etc., as they are created. It is a good idea to save the syntax, re-naming the file using the Save As option on the File menu. Use a name that has some meaning to you, e.g., New_computes. The file will automatically receive the suffix .sps.

Another option for adding new variables to the dataset is to Recode existing variables into new variables. A common example involves grouping an age variable into age categories as shown below, using the variable DAGEQY, which exists on our dataset. DAGEQY is coded in years from 0 to 17, which can be grouped into three age categories:

0 to 5 = 1 – label: “5 years or less”

6 to 12 = 2 – label: “6 to 12 years”

13 to 17 = 3 – label: “13 + years”

The new variable is called age_grp.

From the Transform menu, choose Recode and Into Different Variables as pictured below:

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The following dialog box will open:

Move DAGEQY from the variable list on the left to the box labeled Input Variable -> Output Variable. In the Name slot, enter the new variable name age_grp. Enter Age Categories, the variable label, in the Label slot. Click on Change. The dialog box should look like the one below.

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Click on Old and New Values, and the following dialog box will open:

The next step in grouping the age variable is to specify the existing values of DAGEQY to be recoded. To do this, click on the Range circle under Old Value.

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Once the appropriate slots are open, you have four ranges to enter.

First, enter 0 through 5 in the slots provided under Range. Next, enter the value 1 in the Value slot under New Value. Add is now illuminated.

Clicking on Add produces the following result:

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The specified range appears in the box labeled Old New, and the Range and Value slots have been cleared to permit additional entries.

The three remaining ranges are built in the same manner, adding each specification, until the dialog box looks like the one below.

Click on Continue and return to the previous screen.

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Click on OK to exit the screen. The new variable age_grp has been created. The Recode syntax can be pasted to a syntax file.

The final task is to create the value labels for the new variable age_grp. Labeling variables makes output from statistical reporting procedures much clearer and more elegant.

In the Data Window, go to the column for the new variable age_grp and click in the gray area containing the variable name. The entire column will darken indicating that it has been selected.

Click on the Data menu at the top of the screen to open the following dialog box.

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Click on Define Variable to get to the following dialog box:

The characteristics of age_grp are displayed in this dialog box. Information about the variable type, its label, and its missing values appears here. Click on Labels to get to the following screen:

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In the slot marked Variable Label is the label Age Categories, which was specified during the Recode process. If there is no label for the variable, enter one in this slot.

You can then begin to label the values of age_grp. Enter 1 in the slot marked Value, and enter the label five years or less in the slot marked Value Label. The screen will look like the following:

Add is now illuminated. Click on Add and the text of your command will appear in the central box, clearing the slots for further entries, as in the next screen.

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Build the other two labels until the screen looks like the following:

Click continue, and return to the first screen.

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Click on OK to exit. The labels have been added.

Limiting the Number of Variables

The HCSDB dataset contains many variables. To speed up software performance time, it may be desirable to limit the number of variables for analysis. There are ways to do this.

The first is to Save a subset of variables in a new file with a new name. This option is available only through syntax. The Keep or Drop command lets you save a subset of variables. The choice of Keep or Drop is dependent on which list is shorter to write.

For example, suppose you want to run some procedures to evaluate the rating of health care as it relates to the beneficiaries’ state of health. You are also interested in the differences between military and civilian services, and in differences within these groupings by gender. Moreover, you want to look at regional differences and differences among catchment areas. You can do all the work on a subset of only eight variables, saving them in a separate file.

To write the syntax, open a syntax window. If you want to create a new syntax file, choose New, Syntax on the File menu as in the following:

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A blank syntax window will open.

Write the following command, substituting the file name and directory specification:

SAVE OUTFILE=’C:\MYFILES\HLTHCARE.SAV’/KEEP=SUPREG SEXSMPL REGSMPL WRWT BGCSMPL C00057 C00058 C00015. as in the following:

Upper case is optional. Be sure to enclose the entire file name in single quotes and to type a period at the end of the command.

Run the command by choosing the Run menu and selecting All from the choices.

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Open the new file according to the specifications at the beginning of this chapter.

The second way to limit the number of variables for analysis is to define a subset of variables that will appear in the dialog boxes for procedures. Using the Utility menu, define a subset of variables as in the following:

Select Define Sets.

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Insert a name for the subset of variables in the slot labeled Set Name. Move the variables you want to subset from the list on the left to the slot marked Variables in Set. By way of illustration, we will move the eight variables selected for the day’s processing.

The screen should look like the following:

Click on Add Set to save the set specifications. The screen will change to the following:

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The set is now available for use. To use the set, Close the dialog box, reopen the Utilities menu, choose Use Sets…, and receive this screen:

Move HLTHCARE from the left slot to the right slot, which is labeled Sets in Use. Transfer ALLVARIABLES from the right to the left slot. Leave NEWVARIABLES where it is. OK saves this change.

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Until you change this specification, only eight original variables and any new variables will appear in the dialog boxes associated with procedures.

Limiting the Number of Observations

There are many ways to limit the number of observations available to statistical reporting procedures. The method illustrated here involves using filter variables with a menu-driven Filter By option. Using filters deactivates but does not delete cases from the file. A diagonal line appears next to the filtered cases in the Data Window.

The first task is to compute a filter variable for all the cases in the file.

A filter variable has two values: 0 and 1. The 1 indicates that the case will be included for procedures. The 0 flags the case for removal.

For example, suppose you want to produce a table for people who live in the Southeast, i.e., cases for which the variable REGSMPL = 3. You would build a filter variable named filtr_3, which has the value 1 associated with the cases in the Southeast and 0 for all the other cases in the file. The logic is: if REGSMPL = 3, then filtr_3 = 1, else filtr_3 = 0.

The screen below shows the final step in computing the filter variable. The variable was first initialized to 0 in the same way as 0 was assigned to the new variable, sex_ad. Then, the “If” condition was built for setting the filter variable to 1.

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The screen that follows shows the syntax that was generated as you built the variable filtr_3.

Once you build the filter variable, you can apply it for analyzing only those people from the Southeast.

Using the Data menu, choose Select Cases.

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In the dialog box, check Use filter variable. Move the variable filtr_3 from the variable list on the left side of the dialog box into the slot provided, as indicated below. Check that the option Filtered is checked under Unselected Cases Are. This is the default option.

Click OK and exit the dialog box.

When you return to the Data Window, notice the slanting line next to some of the cases in the file. Those cases have been filtered out.

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You can now produce tables for the subset of cases.

When using filter variables, it is important to check the filter status and to adjust it to fit the present need. Filtered cases are not available for procedures. Moreover, a filter is in effect until it is turned off or until another filter is activated. Check the status line at the bottom of the Data Editor window to see if a filter is activated. In the example above, Filter On is indicated on the status line. To see which filter is active, you must re-enter the Select Cases dialog box. There you can deactivate the filter or activate a new one.

To deactivate a filter, choose All cases and OK as in the screen below.

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Weighting Data

The data file includes a weighting variable, WRWT, which should be applied to all procedure runs. Again, using the Data menu, choose Weight Cases. In the dialog box, choose Weight cases by. Move the weight variable from the list on the left into the slot labeled Frequency Variable on the right as shown below:

Click on OK and exit the dialog box. The indication that the data is weighted appears on the status line near the bottom of the screen. As in the following screen, Weight On is specified there.

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The status line indicates if the data is weighted. Which weight variable is in effect can only be checked by re-entering the Weight Cases dialog box. Weighting stays in effect until it is canceled or until another weight variable is activated.

BUILDING TABLES

Building tables starts with creating a new subset of variables that includes C00057, C00058, C00015, REGSMPL, BGCSMPL, SEXSMPL, XENRLLMT, WRWT, and SUPREG. The procedures Means and Crosstabs will probably meet most of your statistical reporting needs. SPSS also offers many options for editing the output tables themselves. Some of these options are explained here.

Calculating Means

As an example, suppose you want to analyze the health care variables and you want to focus on the New Regions (SUPREG = 1). Suppose you are also interested in overall differences in the mean satisfaction for care received in a military facility as opposed to the mean assessment of the child’s health. Within this grouping, you want to examine the effects of the beneficiary group, BGCSMPL, and sex, SEXSMPL.

The health care variables are C00057 – rating of the health plan, and C00058 – assessment of the child’s health. The statistic you want to see is the mean of the health care variables for each group in our breakdown.

For this analysis, you can use the subset of variables defined above. The subset includes the weight variable, WRWT, which you would activate for procedure runs. The subset also includes new variable, filtr_1, which allows us to select only those cases in the New Regions (SUPREG=1).

Open the Data menu in the Data Window. In the Weight Cases dialog box, activate the weight variable wrwt. Reopen the Data menu and, in the Select Cases dialog box, activate the filter variable, filtr_1. On the status line, Filter On and Weight On should appear.

Open the Statistics menu in the Data Window. Choose Compare Means and Means from the options as illustrated below.

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The dialog box for the Means procedure will open as in the following screen:

Move the health care variables, C00057 and C00058, from the variable list on the left to the box underneath Dependent List. These are the two analysis variables. Notice that Layer 1 of 1 is specified in the middle of the dialog box. Move BGCSMPL from the variable list on the left into the box under Independent List. BGCSMPL is the first grouping variable. The screen should look like the following:

Click on Next in the center of the box to create a second layer. The following screen will open:

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Notice that Layer 2 of 2 is specified in the middle of the dialog box. Move SEXSMPL from the variable list on the left into the box under Independent List. SEXSMPL is the second grouping variable. The screen should look like the following:

To set some options, click on Options and the following dialog box will open:

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On the left of the box is a list of statistics, under Statistics. These are all the possible options for statistical output. In the box under Cell Statistics are the default output statistics for the analysis. In this case, Mean is the statistic of interest. Highlight Number of Cases and Standard Deviation and move them to the box at the left, removing them from the analysis, as follows:

Click on Continue and return to the previous screen. Click OK. The Means procedure will run. On the status line, Running Means will appear, and a counter for the number of cases processed will be activated.

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When Means has finished processing, the Output Navigator window will open automatically. As the name suggests, the output window is not just for looking at output. A number of options are available for navigating through output, moving tables, and even editing the tables themselves.

The output is organized into two sections. On the left side is a navigating tool, which lists the components of the right side, the actual output. In the left pane, Means is indicated, and indented under it appear Title, Notes, Case Processing Summary, and Report. Clicking on Means highlights and selects all the elements. Lines appear around these elements in the right pane. The indenting indicates that the elements are hierarchically organized, with Means at the top. Clicking on any of the sub-elements selects just that element.

A closer look at the left pane reveals another feature. Hiding underneath the element icons are book icons. The books are either open or closed. If a book is closed, the element is hidden. Notice that the book under the Notes icon is closed. This is a default SPSS option. Double-clicking the icon will open the book, and the Notes will appear in the output. Double-clicking an open book will close it, and the physical element will disappear from the output. Closing a book and hiding the element does not delete the element.

It is possible to select elements in the right pane of the output. Simply click anywhere inside of the actual output element, and that element will be selected.

The output may contain many different procedures. The procedure name will be at the top of the list for each section in the left pane. The procedure name does not actually parallel physical output but indicates the category of the output elements.

As you click on each element in the left pane, you will notice that the screen jumps to the actual output of the element, in the right pane. When you click on the procedure name, you jump to the beginning of the next procedure output. This is a quick way to scroll through your output. It also lets you delete, move, and edit selected elements.

To Edit the Title element, Means, to create a more appropriate title, select the table title by clicking once on the Title icon in the left pane. A box now surrounds the title in the right pane. Double-click anywhere within this box, and a box appears around Means, as shown in the following screen.

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You have entered the edit mode for this element, and the cursor appears inside the box. You can delete the word Means and write a title that relates to the information in the table. A possible title appears in the next screen. To exit edit mode, click anywhere outside the box. The change you made will be saved.

If you navigate to the next element, Notes, you see a closed book. Double click this item, and the notes will appear as follows:

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Decide if you want this information to appear in your report. If not, simply double-click the Notes icon, and the notes will again become hidden.

Navigate to Case Processing Summary. Click to bring up the Case Processing Summary table that gives useful information about the number of cases included in and the number of cases excluded from a given procedure. This information is important for the researcher but probably not necessary for the report, so you would delete this item after examining it.

Navigate to Report. Click to see the actual table output from the procedure Means. You can view this table by scrolling through the output. If the table is large, however, scrolling in the output window can be problematic. A better way to review the table is to open it as a Pivot Table Object in a special editor.

Select the table by clicking the Report icon or by clicking inside the table itself. A box will appear around the table. Insert the mouse pointer inside the table and right-click, opening the following dialog box:

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Select SPSS Pivot Table Object and Open as pictured below:

The table will appear in a new screen superimposed on the output. Maximize this screen as shown below.

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In this special editor, there are many options for formatting the table.

Suppose you want to change the table format from vertical to horizontal. Open the Pivot menu in the tool bar and choose Transpose Rows and Columns as shown below:

The rows and columns will be reversed as shown in the following screen. Though the table appears too wide in the viewer, it will fit the page when printed. You can do all the table editing in the left section of the table, and the changes will spread through the entire table.

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You would then notice that certain labels are redundant. The labels, BGCSMPL – BENEFICIARY GROUP and SEXSMPL-SEX are the Variable Labels for the variables. The information in these labels is echoed in the Value Labels, which are also reproduced in the table. You would delete the Variable Labels as follows.

Click inside the section of the table where the label, BGCSMPL – BENEFICIARY GROUP, appears. Right-click to open a dialog box, choosing Hide Dimension Label, as illustrated below.

Click inside the table section labeled SEXSMPLE - SEX and repeat the above procedure. An improved table is shown in the following screen.

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The mean values reported are formatted to allow space for the labels of the health variables. The spaces between the values are not pleasing to the eye. You can shorten these labels and add the lost information in another place, according to the following procedures:

Double-click on the label for child’s health. Delete the text, entering only the words, Child’s Health. Do the same for the health care label, entering only the words, Plan Rating.

Double-click on the word, Report, in the center at the top of the table, right-click, and choose Delete from the dialog box.

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The resulting table is much more readable. You can then add the deleted information to clarify the table output. Double-click on the label Mean at the top left corner of the table, opening the line for editing. Type in a new title for the table. The final result appears below.

After all the editing changes have been made, exit the Pivot Table editor and return to the output navigator. Click on the File menu and choose Print Preview. Zoom in on the page and review the appearance of the report. The page will appear as the page below.

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Calculating Percents

The Crosstabs procedure offers many options for analyzing data. The distribution of cases resulting from “crossing” one variable with another is often of interest. The number of cases, row percentages, column percentages, total percentages, and residuals are easily reproduced by Crosstabs. A full array of statistics is also available.

The examples given here involve examining relationships between variables, with a view toward the number of cases and the percent of cases in cells produced by “crossing” the variables.

For example, suppose you want to see the percentage of people in certain catchment areas who answered “yes” or “no” to the question, “In the last 12 months, did the child see a specialist?” The variables in this analysis are REGSMPL – the catchment area, and C00015 – the question variable. The cases for the analysis are from the Mature Regions.

The first task is to build a new filter variable, assigning 1 to the variable when SUPREG = 2. You would call the variable filtr_2 and build it the same way you built the filter, filtr_3. Cases from the Mature Regions are selected when you activate the filter, and the other cases are filtered out. Check the status line for Filter On. For this table the cases will be unweighted. Using the DATA menu, choose Weight Cases. In the dialog box, choose Do Not Weigh Cases.

Next, open the Statistics menu in the Data Window, choosing Summarize and Crosstabs , as shown below.

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The Crosstabs dialog box will open as follows:

Move C00015 from the variable list on the left into the box marked Row(s):, and move the variable REGSMPL into the box marked Column(s):. The screen will resemble the following:

For this analysis, there are no Layer variables, so you can proceed to format the table cells.

Click on Cells... and open the following dialog box.

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Under Counts, Observed is checked. This refers to the cell count, a statistic you want to see, so you would leave it checked. Under Percentages, check Column because you are interested in the percentage of people in each catchment area. Click Continue and return to the original screen.

Suppose you also want to see the chi-square statistic. Click on Statistics, and the following screen will open:

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Check Chi-square as in the screen above, click Continue to return to the first screen, and click OK to run the procedure. Running Crosstabs will appear on the status line, together with the case counter.

When the run is completed, the output window will open, and you can proceed to reformat the table. For a given work session, SPSS appends new output to previous output--in our case, the Means procedure. As shown in the next screen, a second section now appears in the left pane, headed by the word Crosstabs. Navigate to the Title section and double-click inside the title box to change the text in the box to fit the table, as in the example below.

As you did for the Means procedure, you would again evaluate the Notes and examine the Case Processing Summary. Hide the Notes and delete the Case Processing Summary as you did before.

Navigate to the procedure icon. Follow the procedure for opening an SPSS Pivot Table Object, open the table in the special editor and maximize the screen as in the following:

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The information you requested is in the table, but the table is hard to read. The first possibility is to realign the percent statistic, bringing it into the column dimension. To do this, open the Pivot menu and choose Pivoting Trays, as in the following screen:

The pivoting tool will appear:

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This tool reflects the table structure: rows, columns, and layers. The icons in the margins of the pivoting trays represent the table elements: the variables and the cell statistics. Place the mouse pointer on each icon and notice the element name appear. In this example, on the ROW axis, you would find the variable, C00015 – in last 12 months, did child see specialist, and Statistics – the percent of people in each catchment area. On the column axis is the variable, REGSMPL – the catchment area.

Place the mouse pointer on the Statistics icon. Click and drag the icon from the ROW to the COLUMN dimension. The table immediately reformats as in the following screen:

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Close the pivoting tool and scroll from side to side in the table. Again, the table appears too wide, but the report will print properly. Notice that the table is much more readable.

The label at the top of the table is the Variable Label for REGSMPL. Select it by double-clicking and edit it for clarity (see the screen below).

The table is now formatted to accommodate the long percent label, creating a lot of wasted space. Double-click this element, delete the text, and replace it with the word, “Percent”. The empty space disappears and the table appears as follows:

Next, notice that the label for C00015 is awkward. Select and clear it.

Last, edit the text in the table label so that it better expresses the content of the table. The finished table appears as follows:

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Check Print Preview to see if the table is acceptable.

The last example shows you how to add a Layer dimension to a Crosstabs analysis. Using the same row variable, C00015, suppose you want to look at the percentage of children by their enrollment status in TRICARE Prime, xenrllmt, who saw a specialist in the past 12 months. Suppose you are also interested in sex differences, sexsmpl, among the groupings. Sexsmpl is the Layer variable. You want to remain in the Mature Regions, using filtr_2 as the filter variable. The cases will be weighted by WRWT.

Activate the weight variable, WRWT. The status line indicates Weight On and Filter On. Verify that both the weight and the filter variables are appropriate.

Once more, open the Crosstabs dialog box, enter the analysis variables, and set the Cells options, checking Column under Percentages until the dialog box looks like the following:

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Do the following:

Run Crosstabs.

Edit the Title element in the Output Navigator. Examine Notes and the Case Processing Summary to verify that the CrossTab ran as

expected.

Open the table as an SPSS Pivot Table Object, and the following will appear:

The table is difficult to read, but you can improve it by doing the following.

Select the Pivot menu to activate the Pivoting Trays. The table structure is reproduced in the tool as follows:

Place the mouse pointer on each small icon to find the second grouping variable, SEXSMPL, in the ROW dimension. Move it to the COLUMN dimension, and the table changes to the following:

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Then drag the Statistics icon to the COLUMN dimension to produce the following change:

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Close the Pivoting Trays and hide the dimension label, SEX, in the table. Then, change the percent label to “Percent” and delete the label for C00015 in the row dimension. Last, revise the label above the table to make it more informative.

The resulting table is both clear and informative.

The Print Preview, as in the view below, shows how the report will print.

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CALCULATING VARIANCES OF ESTIMATES

Sampling error occurs when estimates are derived from a sample rather than a complete census of the population. The sample used for a particular survey is only one of a large number of possible samples of the same size and design that could have been selected. Even if the same questionnaire and instructions were used, the estimates from each sample would differ from the others. The standard error (or square root of the variance) indicates the magnitude of the sampling error and thus measures the precision expected from a particular sample.

It is desirable to assess the accuracy of an estimate. The standard error of a survey estimate measures the precision with which an estimate from one sample approximates the true population value. The standard error can then be used to construct confidence intervals for survey parameters, within which the true parameter lies with a measurable degree of certainty.

This section explains how to estimate standard errors or variances for estimators computed from the 2000 Child HCSDB. For a full discussion of variance estimation methods, see Wolter (1985) and references cited therein.

Variance Estimation Methods

To account for the sample design,1 it is customary to use either Taylor series linearization or a resampling method for variance estimation. Neither variance estimation method is, in general, better so the choice of one or the other is largely a matter of convenience. To help users to estimate standard errors using Taylor series linearization or jackknife replication, the public release files for the 2000 Child HCSDB include the following variables:

The stratum variable and the final weight (STRATUM and WRWT) for the Taylor series linearization method

Jackknife replicate weights (WRWT01 to WRWT60) for the jackknife replication method

Two popular software packages are available for performing Taylor series linearization or the jackknife replication method: SUDAANTM (Shah et al. 1996) and WesVarPC (Brick et al. 1996), respectively.2 The discussion below explains how SUDAAN and WesVarPC are used to calculate variance estimates using Taylor series linearization and jackknife replication methods.

1The 2000 HCSDB uses a stratified sampling design. For details, see D.S. Jang et al. “The 2000 Health Care Survey of DoD Beneficiaries: Child Sample Report.” Washington, DC: Mathematica Policy Research, December 2000.

2The latest version for SUDAAN 8.0, can also be used for replication methods including jackknife variance estimation. SAS 8.0 can be used for Taylor series approximation methods.

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Taylor Series Linearization Method

For most sample designs (including the 2000 Child HCSDB), design-based variance estimates for linear estimators of totals or means can be obtained with explicit formulas. However, nonlinear functions such as ratios do not have exact expressions for the variance. The Taylor series linearization method approximates the variance of a nonlinear estimator with the variances of the linear terms from the Taylor series expansion. Woodruff (1971) presented applications of this technique to sample surveys. Details on this method can also be found in “The 2000 Health Care Survey of DoD Beneficiaries: Child Technical Manual”.

To calculate variance estimates based on Taylor series linearization method with HCSDB’s stratified sampling design, both the stratum variable (STRATUM) and the final weight (WRWT) specified for each data record are needed. The public release files for the 2000 Child HCSDB include these variables: STRATUM and WRWT.

SUDAAN incorporates the final analysis weight and the survey design to obtain estimates and their sampling errors. With a small overall sampling rate of about 1 percent, you can use the with-replacement design procedure (STRWR) in calculating standard errors.

All SUDAAN procedures require the following:

The specification of sampling designs. The terminology for the stratified with-replacement sample design is DESIGN = STRWR.

The data file sorted by the variable specified in the NEST statement. For the 2000 Child HCSDB, the data file must be sorted by STRATUM before using any SUDAAN procedure.

A FILE TYPE appropriate for SUDAAN, if you use a stand-alone SUDAAN program. For example, some SUDAAN PC versions under Windows or MS-DOS accept only V6.02 through V6.04 SAS files, and FILE TYPE must be specified as SAS. SAS-callable SUDAAN is also available and can be invoked directly in a SAS program with any available SAS file as input; FILE TYPE is not needed here.

The WEIGHT variable for 2000, which is WRWT

The following program is an example of how to use SUDAAN to calculate variance estimates for a mean statistic. Suppose you want to estimate:

The health plan rating (C00057) among all beneficiaries in the past 12 months who saw a specialist (C00015=1) for each region (SUPREG)

PROC DESCRIPT DATA=HCSDB00 /*FILETYPE=SAS*/ DESIGN=STRWR;WEIGHT WRWT;NEST STRATUM;SUBPOPN C00015=1;SUBGROUP SUPREG;LEVELS 16;VAR C00057;

The following program is an example of how to use SUDAAN to calculate variance estimates for column percentages or row percentages. Suppose you want to estimate:

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A cross tabulation of children in region 3 who in the past 12 months most often used a military facility, a civilian facility, or used no health care (C00043) by TRICARE enrollment (XENRLLMT).

PROC CROSSTAB DATA=HCSDB00 /*FILETYPE=SAS*/ DESIGN=STRWR;WEIGHT WRWT;NEST STRATUM;SUBPOPN SUPREG = 3;SUBGROUP C00043 XENRLLMT;LEVELS 3 5;TABLES C00043 *XENRLLMT;

From the above examples, users should note that:

PROC DESCRIPT can be used to compute estimates of means and the corresponding standard errors.

PROC CROSSTAB can be used to compute estimates of proportions and the corresponding standard errors.

For a more detailed and complete discussion of how to use SUDAAN, see Shah et al. (1996).

Jackknife Replication Method

Another popular way to estimate the variance is to use a resampling method such as jackknife replication, balanced repeated replication, random groups, or the bootstrap method. Like other replication methods, jackknife replication constructs a number of subsamples (replicates) from the full sample and computes the statistics of interest for each replicate (with the same formula as the full sample estimate). The mean square error of the replicate estimates around their corresponding full estimate provides an estimate of the sampling variance of the statistic of interest regardless of the functional form of the statistic.

There are 60 replicate weights (WRWT01-WRWT60) for the 2000 Child HCSDB in the public use file. Construction of these weights is described in the Child Technical Manual. With the replicate weights, you can produce jackknife standard errors using in-house or custom written software, or you can use a publicly available software package such as WesVarPC or SUDAAN 7.5. Because WesVarPC 2.02 is available as freeware on the World Wide Web (http://www.wesvar/licensing/index.html), the following example explains how it is used to produce jackknife variance estimates for statistics from the 2000 Child HCSDB.

Suppose you want to estimate the mean rating of specialists (C00016) by beneficiaries whose child went to a specialist in the past 12 months (C00015=1) for each region (SUPREG). You would use WesVarPc as follows.

Create a SAS V6.04 file, SAS Transport file, or ASCII file. WesVarPC has a restriction for the input data format. All files must be converted to one of these three types of files before being imported to WesVarPC.

Create a WesVarPC data file. From the Prep menu, choose the Import Data Files screen and import all variables for the analysis. For this example, input C00015, and SUPREG into the Variables box, WRWT01-WRWT60 into the Replicates box, and MPRID into the ID box. Also specify the replication method as JK1 on this screen.

Create a data file for the subpopulation. Specify the subpopulation by choosing the Subpop WesVarPC Data File from the Prep menu: C00015=1.

Calculate estimates. From the Tables menu, choose New and select the file created from the above procedure. Then, from the Table Request screen, specify C00015=1 as the

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Analysis variable, MEAN (C00016) as the Compute Statistics, and REGSMPL C00016 Table.

The above steps can also be followed to produce standard errors. The WesVarPC user’s manual (Brick et al. 1996) provides other possible methods for producing standard errors. The latest WesVarPC 4.0 is no longer freeware and can be purchased from Westat.

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CodebookThis chapter describes every variable in the database. This codebook will also be helpful in identifying which data are available for various analyses, and what, if any, recoding of variables will benefit your needs. It may also be useful in reviewing output.

The variables are in order based on their position in the database. An alphabetical listing (see Table of Contents) is provided to assist in locating variables.

The codebook contains frequency distributions for both discrete and continuous variables. A discrete variable is one that has only a few values. A continuous variable may have many possible values.

Below are two examples of the presentation of variables in the codebook. For each variable, we include the variable name, definition, weighted and unweighted frequency distributions, and the format value for each value. The first example contains a frequency distribution for a discrete variable.

C00057 - Rating of exprience with child hlth plan

Unweighted WeightedValue Count Percent Count Percent Formatted Value

A 24 0.22 2789 0.16 Mult response. 322 2.99 53436 3.09 No response0 184 1.71 28313 1.64 0 Worst plan1 131 1.22 18896 1.09 12 232 2.16 36918 2.14 23 306 2.84 45527 2.63 34 346 3.21 54571 3.16 45 1241 11.53 201021 11.63 56 882 8.19 140555 8.13 67 1624 15.09 265034 15.33 78 2236 20.77 368444 21.32 89 1735 16.12 277076 16.03 910 1501 13.94 235827 13.64 10 Best plan

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Chapter

4


The table below contains an example of a frequency distribution for a continuous variable: final weight. The frequency does not list every possible value of final weight individually but instead shows several age ranges that together cover all possible values of final weight. You will notice that the last range representing the final weight with range 240,671 to 264,202 includes 682 sponsors in this range.

WRWT - Final Weight


39.340 -- 52.567 1288 11.97 60385 3.49 Minimum to 10th Percentile

52.683 -- 66.042 1430 13.29 86649 5.01 >10th to 25th Percentile66.746 -- 197.198 2870 26.66 434328 25.13 >25th to 50th Percentile197.887 -- 215.087 2096 19.47 430147 24.89 >50th to 75th Percentile215.644 -- 239.243 2398 22.28 544125 31.48 >75th to 90th Percentile240.671 -- 264.202 682 6.34 172772 10.00 >90th to 100th Percentile

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MPRID - Unique MPR Identifier


00000014 -- 01881786 10764 100.00 1728407 100.00 00000001--99999999

MPCSMPL - MPCSMPL - Military Personnel Category


1 7829 72.73 1245439 72.06 Enlisted/Unknown2 2619 24.33 431251 24.95 Officer3 316 2.94 51716 2.99 Warrant Officer

SVCSMPL - SVCSMPL - Branch of Service


1 3644 33.85 579021 33.50 Army2 2964 27.54 474448 27.45 Navy3 2890 26.85 489616 28.33 Air Force4 802 7.45 122534 7.09 Marine Corps5 383 3.56 49198 2.85 Coast Guard6 81 0.75 13591 0.79 Other/Unknown

SEXSMPL - SEXSMPL - Sex


1 5562 51.67 896425 51.86 Male2 5202 48.33 831982 48.14 Female

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AGESMPL - AGESMPL - Age


1 3309 30.74 523303 30.28 5 years or less2 4002 37.18 687356 39.77 6 to 12 years3 3453 32.08 517748 29.96 13 years or more

BGCSMPL - BGCSMPL - Beneficiary Group


1 8 0.07 1634 0.09 Active Duty2 6542 60.78 1069253 61.86 Family of Active3 4213 39.14 657443 38.04 Ret/Surv/Fam <654 1 0.01 76 0.00 Ret/Surv/Fam 65+

REGSMPL - REGSMPL - Region


1 1458 13.55 239175 13.84 Northeast2 1115 10.36 198215 11.47 Mid-Atlantic3 1450 13.47 212786 12.31 Southeast4 914 8.49 128783 7.45 Gulfsouth5 1111 10.32 157661 9.12 Heartland6 1270 11.80 207030 11.98 Southwest7 429 3.99 74299 4.30 Central 78 1008 9.36 176502 10.21 Central 89 874 8.12 140855 8.15 Southern California10 334 3.10 50689 2.93 Golden Gate11 500 4.65 82369 4.77 Northwest12 200 1.86 39216 2.27 Hawaii16 101 0.94 20827 1.20 Alaska

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ENBGSMPL - Enrollment by beneficiary category


1 8 0.07 1634 0.09 Active duty2 1940 18.02 125465 7.26 Active duty fam,Prime,civ

PCM3 3445 32.00 720182 41.67 Active duty fam,Prime,mil

PCM4 1158 10.76 223682 12.94 Active duty fam,non-

enrollee5 1411 13.11 80270 4.64 Retired,<65,civ PCM6 952 8.84 188480 10.90 Retired,<65,mil PCM7 1850 17.19 388693 22.49 Retired,<65,non-enrollee

STRATUM - Sampling STRATUM


111 486 4.52 97507 5.64 111112 542 5.04 116356 6.73 112113 367 3.41 72069 4.17 113121 332 3.08 19579 1.13 121122 392 3.64 25402 1.47 122123 401 3.73 16974 0.98 123131 312 2.90 53516 3.10 131132 403 3.74 102471 5.93 132133 471 4.38 93891 5.43 133211 483 4.49 116087 6.72 211212 520 4.83 120646 6.98 212213 352 3.27 68589 3.97 213221 305 2.83 23403 1.35 221222 383 3.56 29396 1.70 222223 411 3.82 21219 1.23 223231 243 2.26 37244 2.15 231232 284 2.64 61791 3.58 232233 299 2.78 63757 3.69 233311 476 4.42 107529 6.22 311312 603 5.60 124912 7.23 312313 465 4.32 77840 4.50 313321 371 3.45 19526 1.13 321322 403 3.74 26043 1.51 322323 432 4.01 19935 1.15 323331 264 2.45 40905 2.37 331332 339 3.15 83231 4.82 332333 425 3.95 88591 5.13 333

SUPREG - SUPREG - Super Region

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1 3684 34.23 595051 34.43 New regions-1,2,52 3279 30.46 540986 31.30 Mature regions-6,9-12,163 3801 35.31 592370 34.27 Other regions-3,4,7/8

MRTLSTAT - Marital Status


9462 87.90 1521604 88.04 MissingN 9 0.08 1830 0.11 Never MarriedZ 1293 12.01 204973 11.86 Unknown

RACEETHN - Race/Ethnic Code


9612 89.30 1549013 89.62 MissingB 1 0.01 215 0.01 Asian or Pacific IslanderC 2 0.02 334 0.02 Black(not Hispanic)D 16 0.15 3179 0.18 White(not Hispanic)Z 1133 10.53 175666 10.16 Unknown

DAGEQY - Age (As of 31 January 2001)


0 560 5.20 90333 5.23 Less than 1 yr001 -- 002 1082 10.05 166975 9.66 001--002003 -- 005 1667 15.49 265994 15.39 003--005006 -- 012 4002 37.18 687356 39.77 006--012013 -- 017 3453 32.08 517748 29.96 013--017

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FIELDAGE - Age (As of 1 July 2001)


0 313 2.91 50898 2.94 Less than 1 yr001 -- 002 1090 10.13 169355 9.80 001--002003 -- 005 1672 15.53 266230 15.40 003--005006 -- 012 3984 37.01 680139 39.35 006--012013 -- 017 3482 32.35 528301 30.57 013--017

18 223 2.07 33484 1.94 18 yrs

PCM - Primary Manager Code (CIV or MIL)


3015 28.01 613843 35.51 Missing/UnknownCIV 3351 31.13 205736 11.90 TRICARE enrollee w/civ

PCMMTF 4398 40.86 908829 52.58 TRICARE enrollee w/mil

PCM

TSPSITE - TSP Site (regardless of age)


9653 89.68 1519407 87.91 Does not live in a TSP Catchment Area

COSPRINGS 175 1.63 31997 1.85 Fort Evans-Carson ACH & USAF Academy

DOVER 41 0.38 8348 0.48 Dover AFBKEESLER 62 0.58 11908 0.69 Keesler AFBMADIGAN 162 1.51 30605 1.77 Fort Lewis-Madigan AMCREYSHEP 94 0.87 18476 1.07 Fort Sill-Reynolds ACH &

Sheppart AFBSANANTONIO 215 2.00 43861 2.54 Fort Sam Houston-

Brooke/Lackland-WilfordSANDIEGO 362 3.36 63806 3.69 NMC San Diego

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LEGDDSCD - DDS Code


1 10754 99.91 1726378 99.88 Dependent Child20 8 0.07 1634 0.09 Sponsor30 2 0.02 394 0.02 Spouse of Sponsor

PNLCATCD - Personnel Category Code (Duty Status)


A 5789 53.78 973958 56.35 Active dutyN 482 4.48 63256 3.66 National GuardQ 1 0.01 262 0.02 Reserve retireeR 4128 38.35 643123 37.21 RetiredT 1 0.01 262 0.02 Foreign militaryV 363 3.37 47546 2.75 Reserve

MBRRELCD - Member Relationship Code


A 8 0.07 1634 0.09 SelfB 2 0.02 394 0.02 SpouseC 10654 98.98 1709339 98.90 Child or stepchildE 100 0.93 17039 0.99 Ward (court ordered)

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DBENCAT - Beneficiary Category


ACT 2 0.02 382 0.02 Active DutyDA 5704 52.99 960049 55.55 Dependent of Active Duty

DGR 838 7.79 109204 6.32 Dependent of Guard/Reserve

DR 4046 37.59 630589 36.48 Dependent of RetireeDS 129 1.20 20334 1.18 Survivor

GRD 6 0.06 1252 0.07 Guard/ReserveOTH 38 0.35 6521 0.38 Other

Z 1 0.01 76 0.00 Unknown

DMEDELG - Medical Privlege Code


1 12 0.11 2484 0.14 Direct Care Only2 10420 96.80 1702027 98.47 Direct Care and

CHAMPUS4 36 0.33 6380 0.37 Transitional Direct Care

Only5 2 0.02 354 0.02 Transitional Direct Care

and CHAMPUSU 294 2.73 17162 0.99 Unknown

DSPONSVC - Derived Sponsor Branch of Service


A 3644 33.85 579021 33.50 ArmyC 383 3.56 49198 2.85 Coast GuardF 2890 26.85 489616 28.33 Air ForceM 802 7.45 122534 7.09 Marine CorpsN 2306 21.42 363469 21.03 NavyV 658 6.11 110979 6.42 Navy AfloatX 81 0.75 13591 0.79 Other

05/18/23 95


MEDTYPE - Medicare Type


10762 99.98 1728297 99.99 Neither A nor B applyA 1 0.01 64 0.00 Eligible for Medicare AB 1 0.01 46 0.00 Eligible for Medicare B

PATCAT - Aggregated Beneficiary Category


ACTDTY 8 0.07 1634 0.09 Active Duty and Guard/Reserve

DEPACT 6542 60.78 1069253 61.86 Dependent of Active Duty & Guard/Reserve

NADD<65 4213 39.14 657443 38.04 Retiree/Depend of Retir/Surviv/Other <65

UNKNOWN 1 0.01 76 0.00 Unknown

ENRID - Enrollment DMISID


3015 28.01 613843 35.51 1 7 0.07 1483 0.09 13 33 0.31 6279 0.36 34 35 0.33 7002 0.41 45 13 0.12 2946 0.17 56 37 0.34 8189 0.47 68 23 0.21 4632 0.27 89 33 0.31 6052 0.35 910 32 0.30 6156 0.36 1013 24 0.22 5357 0.31 1314 51 0.47 11030 0.64 1415 11 0.10 2573 0.15 1518 19 0.18 4195 0.24 1819 15 0.14 3193 0.18 1924 43 0.40 9191 0.53 2426 35 0.33 7889 0.46 2628 23 0.21 5100 0.30 2829 58 0.54 12597 0.73 2930 12 0.11 2703 0.16 3032 56 0.52 11391 0.66 3233 50 0.46 9869 0.57 3335 24 0.22 4866 0.28 3536 31 0.29 6425 0.37 36

05/18/23 96


37 13 0.12 2613 0.15 3738 47 0.44 9145 0.53 3839 74 0.69 14288 0.83 3942 58 0.54 11499 0.67 4243 23 0.21 4588 0.27 4345 46 0.43 8840 0.51 4546 22 0.20 4115 0.24 4647 41 0.38 8220 0.48 4748 38 0.35 7312 0.42 4849 43 0.40 8573 0.50 4950 17 0.16 3322 0.19 5051 27 0.25 5337 0.31 5152 44 0.41 9732 0.56 5253 19 0.18 3928 0.23 5355 60 0.56 12110 0.70 5556 37 0.34 7512 0.43 5657 47 0.44 9810 0.57 5758 38 0.35 7714 0.45 5859 14 0.13 2715 0.16 5960 70 0.65 13983 0.81 6061 42 0.39 8508 0.49 6162 17 0.16 3814 0.22 6264 15 0.14 3421 0.20 6466 46 0.43 9467 0.55 6667 35 0.33 7229 0.42 6768 10 0.09 2077 0.12 6869 39 0.36 7934 0.46 6973 49 0.46 9973 0.58 7374 9 0.08 1714 0.10 7475 28 0.26 5849 0.34 7576 22 0.20 4164 0.24 7677 13 0.12 2680 0.16 7778 50 0.46 10261 0.59 7879 52 0.48 10209 0.59 7981 11 0.10 2287 0.13 8183 22 0.20 4209 0.24 8384 10 0.09 2144 0.12 8485 15 0.14 2994 0.17 8586 9 0.08 1864 0.11 8689 30 0.28 6152 0.36 8990 9 0.08 1842 0.11 9091 69 0.64 13645 0.79 9192 21 0.20 4343 0.25 9293 3 0.03 620 0.04 9394 14 0.13 2957 0.17 9495 74 0.69 15370 0.89 9596 30 0.28 6649 0.38 9697 12 0.11 2704 0.16 9798 38 0.35 8480 0.49 98100 17 0.16 3525 0.20 100101 20 0.19 4074 0.24 101103 9 0.08 1921 0.11 103104 26 0.24 4958 0.29 104105 39 0.36 7590 0.44 105106 9 0.08 1638 0.09 106107 6 0.06 1321 0.08 107108 37 0.34 7212 0.42 108

05/18/23 97


109 45 0.42 9835 0.57 109110 80 0.74 17553 1.02 110112 23 0.21 5061 0.29 112113 29 0.27 6278 0.36 113114 9 0.08 1976 0.11 114117 67 0.62 14665 0.85 117118 20 0.19 4243 0.25 118119 29 0.27 5558 0.32 119120 47 0.44 9210 0.53 120121 29 0.27 5982 0.35 121122 16 0.15 3285 0.19 122123 64 0.59 13335 0.77 123124 52 0.48 10725 0.62 124125 81 0.75 18054 1.04 125126 39 0.36 8795 0.51 126127 33 0.31 6962 0.40 127128 15 0.14 3275 0.19 128129 16 0.15 3193 0.18 129131 16 0.15 3543 0.20 131190 79 0.73 4272 0.25 190191 24 0.22 1334 0.08 191192 18 0.17 1152 0.07 192193 50 0.46 2746 0.16 193194 18 0.17 1097 0.06 194196 13 0.12 901 0.05 196197 6 0.06 359 0.02 197198 65 0.60 3715 0.21 198199 21 0.20 1415 0.08 199203 9 0.08 2046 0.12 203209 1 0.01 233 0.01 209210 2 0.02 427 0.02 210231 2 0.02 427 0.02 231232 13 0.12 2980 0.17 232247 7 0.07 1448 0.08 247248 11 0.10 2349 0.14 248250 1 0.01 194 0.01 250252 25 0.23 4860 0.28 252261 5 0.05 971 0.06 261269 4 0.04 926 0.05 269272 8 0.07 1547 0.09 272273 17 0.16 3250 0.19 273275 3 0.03 617 0.04 275280 30 0.28 6497 0.38 280281 6 0.06 1398 0.08 281285 17 0.16 3836 0.22 285287 13 0.12 2786 0.16 287297 1 0.01 228 0.01 297299 9 0.08 1681 0.10 299301 3 0.03 602 0.03 301306 20 0.19 4135 0.24 306308 16 0.15 3209 0.19 308309 6 0.06 1242 0.07 309310 15 0.14 2921 0.17 310316 1 0.01 206 0.01 316317 6 0.06 1002 0.06 317319 6 0.06 1044 0.06 319321 3 0.03 657 0.04 321

05/18/23 98


322 1 0.01 198 0.01 322326 21 0.20 4063 0.24 326327 3 0.03 561 0.03 327330 24 0.22 4904 0.28 330335 13 0.12 2671 0.15 335337 21 0.20 3864 0.22 337338 4 0.04 656 0.04 338352 11 0.10 2085 0.12 352356 28 0.26 5443 0.31 356363 4 0.04 900 0.05 363364 13 0.12 2980 0.17 364365 5 0.05 1128 0.07 365366 32 0.30 6890 0.40 366369 4 0.04 896 0.05 369372 3 0.03 596 0.03 372378 61 0.57 12405 0.72 378385 45 0.42 9035 0.52 385386 4 0.04 818 0.05 386387 28 0.26 5856 0.34 387390 6 0.06 1238 0.07 390395 9 0.08 1987 0.11 395401 1 0.01 239 0.01 401405 32 0.30 6347 0.37 405407 10 0.09 2259 0.13 407413 12 0.11 2398 0.14 413437 21 0.20 4807 0.28 437508 3 0.03 638 0.04 508511 17 0.16 3330 0.19 511517 2 0.02 434 0.03 517606 2 0.02 420 0.02 606607 2 0.02 439 0.03 607609 2 0.02 429 0.02 609610 2 0.02 478 0.03 610611 1 0.01 206 0.01 611612 1 0.01 167 0.01 612614 4 0.04 750 0.04 614617 1 0.01 228 0.01 617621 2 0.02 472 0.03 621622 3 0.03 639 0.04 622623 1 0.01 167 0.01 623624 3 0.03 677 0.04 624625 1 0.01 198 0.01 625629 1 0.01 228 0.01 629633 3 0.03 626 0.04 633635 3 0.03 611 0.04 635640 3 0.03 697 0.04 640656 3 0.03 662 0.04 656800 2 0.02 426 0.02 800802 1 0.01 239 0.01 802804 2 0.02 438 0.03 804805 5 0.05 1079 0.06 805806 4 0.04 845 0.05 806808 2 0.02 434 0.03 808814 1 0.01 239 0.01 814825 1 0.01 228 0.01 825852 2 0.02 445 0.03 852855 1 0.01 198 0.01 855

05/18/23 99


871 1 0.01 216 0.01 871872 1 0.01 239 0.01 872953 2 0.02 437 0.03 953971 1 0.01 239 0.01 971972 1 0.01 192 0.01 972983 1 0.01 194 0.01 9831003 2 0.02 474 0.03 10031013 2 0.02 461 0.03 10131014 1 0.01 216 0.01 10141015 1 0.01 216 0.01 10151016 2 0.02 421 0.02 10161017 3 0.03 660 0.04 10171124 1 0.01 246 0.01 11241126 1 0.01 198 0.01 11261147 1 0.01 206 0.01 11471170 3 0.03 667 0.04 11701179 1 0.01 198 0.01 11791269 1 0.01 228 0.01 12691316 14 0.13 2748 0.16 13161560 3 0.03 650 0.04 15601562 1 0.01 217 0.01 15621563 1 0.01 167 0.01 15631564 1 0.01 167 0.01 15641581 1 0.01 167 0.01 15811587 1 0.01 194 0.01 15871592 11 0.10 2518 0.15 15921656 4 0.04 951 0.05 16566200 43 0.40 8909 0.52 62006201 58 0.54 11984 0.69 62016207 55 0.51 12011 0.69 62076214 46 0.43 9204 0.53 62146215 41 0.38 8849 0.51 62156216 21 0.20 4462 0.26 62166221 45 0.42 9210 0.53 62216903 524 4.87 30077 1.74 69036904 394 3.66 22257 1.29 69046906 418 3.88 28666 1.66 69066907 65 0.60 3950 0.23 69076908 168 1.56 9965 0.58 69086909 315 2.93 22632 1.31 69096910 138 1.28 9180 0.53 69106911 157 1.46 10670 0.62 69116912 21 0.20 1511 0.09 69127032 1 0.01 179 0.01 70327138 8 0.07 1845 0.11 71387139 29 0.27 5633 0.33 71397143 20 0.19 4031 0.23 71437236 17 0.16 3747 0.22 72367239 4 0.04 856 0.05 72397286 18 0.17 3736 0.22 72867294 50 0.46 10383 0.60 72947297 2 0.02 374 0.02 72978001 94 0.87 5550 0.32 80018002 60 0.56 3480 0.20 80028003 128 1.19 7368 0.43 80038004 119 1.11 6947 0.40 80048005 66 0.61 3885 0.22 8005

05/18/23 100


8006 134 1.24 7661 0.44 80068007 18 0.17 1030 0.06 80078008 3 0.03 171 0.01 80088009 36 0.33 2181 0.13 80098010 77 0.72 4391 0.25 80108011 40 0.37 2229 0.13 80118012 7 0.07 401 0.02 80128013 4 0.04 228 0.01 80138015 8 0.07 475 0.03 80158016 41 0.38 2588 0.15 80168018 22 0.20 1251 0.07 80188907 1 0.01 198 0.01 89078924 1 0.01 233 0.01 89248939 1 0.01 199 0.01 89398977 2 0.02 441 0.03 89778982 1 0.01 206 0.01 89828987 2 0.02 431 0.02 89878995 2 0.02 411 0.02 8995

DCATCH - Catchment Area


3 50 0.46 9108 0.53 35 35 0.33 7790 0.45 56 48 0.45 9960 0.58 69 86 0.80 12801 0.74 914 120 1.11 20266 1.17 1424 186 1.73 27650 1.60 2428 43 0.40 7778 0.45 2829 361 3.35 63611 3.68 2930 20 0.19 3675 0.21 3032 72 0.67 13265 0.77 3233 103 0.96 18732 1.08 3337 96 0.89 15077 0.87 3738 116 1.08 16739 0.97 3839 250 2.32 36243 2.10 3942 137 1.27 24268 1.40 4245 135 1.25 16505 0.95 4547 66 0.61 12799 0.74 4748 77 0.72 14220 0.82 4849 86 0.80 14835 0.86 4952 190 1.77 37809 2.19 5253 23 0.21 4408 0.26 5355 110 1.02 17813 1.03 5556 64 0.59 11088 0.64 5657 55 0.51 11119 0.64 5760 195 1.81 25509 1.48 6061 72 0.67 12408 0.72 6164 27 0.25 5278 0.31 6466 95 0.88 17408 1.01 6667 136 1.26 23550 1.36 6773 62 0.58 11908 0.69 7375 50 0.46 9410 0.54 75

05/18/23 101


78 86 0.80 14950 0.86 7879 78 0.72 13907 0.80 7986 22 0.20 3446 0.20 8689 198 1.84 34755 2.01 8991 113 1.05 20166 1.17 9192 37 0.34 6197 0.36 9295 84 0.78 16708 0.97 9598 60 0.56 11255 0.65 98101 29 0.27 5683 0.33 101103 75 0.70 14679 0.85 103104 32 0.30 5232 0.30 104105 66 0.61 10704 0.62 105108 58 0.54 10717 0.62 108109 114 1.06 23163 1.34 109110 195 1.81 34007 1.97 110113 34 0.32 7221 0.42 113117 100 0.93 20481 1.18 117120 77 0.72 13570 0.79 120121 69 0.64 12106 0.70 121123 263 2.44 52576 3.04 123124 430 3.99 81500 4.72 124125 161 1.50 30390 1.76 125126 79 0.73 15197 0.88 126127 45 0.42 8900 0.51 127131 19 0.18 3943 0.23 131781 4 0.04 620 0.04 781782 33 0.31 4733 0.27 782783 15 0.14 1852 0.11 783784 80 0.74 14400 0.83 784785 100 0.93 18119 1.05 785786 16 0.15 2540 0.15 786787 1 0.01 209 0.01 787788 27 0.25 5426 0.31 788789 2 0.02 302 0.02 789901 175 1.63 24670 1.43 901902 18 0.17 3077 0.18 902904 113 1.05 16111 0.93 904906 101 0.94 10577 0.61 906907 58 0.54 11220 0.65 907908 43 0.40 8597 0.50 908911 335 3.11 45450 2.63 911912 10 0.09 1408 0.08 912914 49 0.46 6536 0.38 914915 86 0.80 10274 0.59 915917 96 0.89 16979 0.98 917918 53 0.49 6943 0.40 918920 97 0.90 9553 0.55 920921 55 0.51 9088 0.53 921922 85 0.79 12705 0.74 922923 124 1.15 14774 0.85 923924 54 0.50 10602 0.61 924925 77 0.72 10444 0.60 925927 29 0.27 5839 0.34 927928 19 0.18 3800 0.22 928929 18 0.17 2981 0.17 929930 21 0.20 3189 0.18 930931 95 0.88 14879 0.86 931

05/18/23 102


932 89 0.83 15774 0.91 932933 151 1.40 21541 1.25 933934 123 1.14 18952 1.10 934935 39 0.36 7264 0.42 935936 150 1.39 17160 0.99 936937 126 1.17 20760 1.20 937938 73 0.68 8175 0.47 938939 178 1.65 25071 1.45 939940 26 0.24 4985 0.29 940941 38 0.35 4892 0.28 941942 26 0.24 4896 0.28 942943 135 1.25 13837 0.80 943945 91 0.85 14787 0.86 945946 17 0.16 2922 0.17 946948 134 1.24 18303 1.06 948950 74 0.69 11561 0.67 950951 29 0.27 5437 0.31 951973 8 0.07 1404 0.08 973974 28 0.26 4611 0.27 974985 171 1.59 22645 1.31 985986 272 2.53 39436 2.28 986987 261 2.42 31543 1.82 987988 53 0.49 7888 0.46 988989 108 1.00 9715 0.56 989990 68 0.63 10949 0.63 990993 433 4.02 57804 3.34 993995 16 0.15 2747 0.16 995996 68 0.63 10967 0.63 996

ULOCDMIS - Unit DMISID


4275 39.72 666542 38.56 3 25 0.23 4999 0.29 35 27 0.25 5384 0.31 56 33 0.31 6974 0.40 69 29 0.27 4556 0.26 914 56 0.52 8869 0.51 1424 103 0.96 16052 0.93 2428 25 0.23 4410 0.26 2829 288 2.68 47389 2.74 2930 21 0.20 3733 0.22 3032 51 0.47 9605 0.56 3233 42 0.39 8271 0.48 3337 130 1.21 22758 1.32 3738 69 0.64 10866 0.63 3839 135 1.25 21463 1.24 3942 91 0.85 16469 0.95 4245 52 0.48 7153 0.41 4547 31 0.29 5844 0.34 4748 58 0.54 10486 0.61 4849 56 0.52 9930 0.57 4952 161 1.50 31665 1.83 52

05/18/23 103


53 19 0.18 3518 0.20 5355 74 0.69 11873 0.69 5556 49 0.46 7627 0.44 5657 50 0.46 10117 0.59 5760 131 1.22 18197 1.05 6061 58 0.54 9838 0.57 6164 20 0.19 4104 0.24 6466 103 0.96 20092 1.16 6667 92 0.85 16788 0.97 6773 77 0.72 12442 0.72 7375 31 0.29 6084 0.35 7578 55 0.51 10239 0.59 7879 28 0.26 5114 0.30 7986 8 0.07 1513 0.09 8689 163 1.51 29216 1.69 8991 88 0.82 14880 0.86 9192 23 0.21 4221 0.24 9293 4 0.04 684 0.04 9395 44 0.41 8812 0.51 9598 40 0.37 8526 0.49 98101 15 0.14 3088 0.18 101103 40 0.37 7500 0.43 103104 26 0.24 4688 0.27 104105 47 0.44 7986 0.46 105108 36 0.33 5764 0.33 108109 69 0.64 13088 0.76 109110 143 1.33 25439 1.47 110112 20 0.19 4095 0.24 112113 29 0.27 5792 0.34 113117 57 0.53 11350 0.66 117120 54 0.50 9567 0.55 120121 26 0.24 4535 0.26 121123 78 0.72 13783 0.80 123124 374 3.47 67540 3.91 124125 88 0.82 17206 1.00 125126 56 0.52 10790 0.62 126127 43 0.40 8276 0.48 127131 21 0.20 4354 0.25 131620 1 0.01 201 0.01 620781 1 0.01 43 0.00 781782 5 0.05 400 0.02 782784 45 0.42 7260 0.42 784785 52 0.48 9538 0.55 785786 14 0.13 1989 0.12 786901 86 0.80 12806 0.74 901902 12 0.11 2147 0.12 902904 41 0.38 5912 0.34 904906 47 0.44 3767 0.22 906907 48 0.45 8908 0.52 907908 25 0.23 4604 0.27 908911 157 1.46 21429 1.24 911912 2 0.02 154 0.01 912914 10 0.09 1019 0.06 914915 43 0.40 3708 0.21 915916 10 0.09 2121 0.12 916917 51 0.47 9209 0.53 917918 11 0.10 1169 0.07 918

05/18/23 104


920 52 0.48 5978 0.35 920921 44 0.41 7392 0.43 921922 39 0.36 5915 0.34 922923 50 0.46 4644 0.27 923924 37 0.34 6586 0.38 924925 43 0.40 4971 0.29 925927 21 0.20 4339 0.25 927928 7 0.07 1384 0.08 928929 5 0.05 850 0.05 929930 9 0.08 1019 0.06 930931 65 0.60 8912 0.52 931932 48 0.45 8668 0.50 932933 94 0.87 11919 0.69 933934 43 0.40 6890 0.40 934935 26 0.24 4875 0.28 935936 56 0.52 5701 0.33 936937 77 0.72 12692 0.73 937938 35 0.33 2815 0.16 938939 67 0.62 6986 0.40 939940 15 0.14 2700 0.16 940941 1 0.01 167 0.01 941942 14 0.13 2805 0.16 942943 52 0.48 5038 0.29 943945 51 0.47 8134 0.47 945946 5 0.05 830 0.05 946948 52 0.48 7532 0.44 948950 29 0.27 3802 0.22 950951 19 0.18 3487 0.20 951953 3 0.03 473 0.03 953974 7 0.07 1273 0.07 974985 68 0.63 9171 0.53 985986 118 1.10 19650 1.14 986987 57 0.53 7006 0.41 987988 25 0.23 3688 0.21 988989 71 0.66 7365 0.43 989990 34 0.32 5943 0.34 990993 155 1.44 19857 1.15 993995 3 0.03 128 0.01 995996 47 0.44 5995 0.35 996999 322 2.99 52306 3.03 999

ENLSMPL - ENLSMPL - Enrollment Sampling Group


1 4398 40.86 908829 52.58 Enrolled-Mil PCM2 3351 31.13 205736 11.90 Enrolled-Civ PCM3 3015 28.01 613843 35.51 Not enrolled

FNSTATUS - Final Status

Unweighted Weighted05/18/23 105


Value Count Percent Count Percent Formatted Value

11 10764 100.00 1728407 100.00 Elig,return complete

KEYCOUNT - # of Key Questions Answered


14 3 0.03 592 0.03 1415 17 0.16 2289 0.13 1516 5 0.05 719 0.04 1617 8 0.07 1014 0.06 1718 16 0.15 2508 0.15 1819 70 0.65 11568 0.67 1920 26 0.24 4138 0.24 2021 37 0.34 5433 0.31 2122 55 0.51 8784 0.51 2223 124 1.15 18838 1.09 2324 121 1.12 20223 1.17 2425 270 2.51 44451 2.57 2526 1294 12.02 213528 12.35 2627 8718 80.99 1394322 80.67 27

POSTSTR - Post Stratification Cell


111 522 4.85 101809 5.89 111112 552 5.13 115524 6.68 112113 340 3.16 69483 4.02 113121 329 3.06 20195 1.17 121122 394 3.66 24598 1.42 122123 353 3.28 16761 0.97 123131 321 2.98 55308 3.20 131132 398 3.70 97436 5.64 132133 475 4.41 93937 5.43 133211 511 4.75 118315 6.85 211212 538 5.00 120792 6.99 212213 338 3.14 67508 3.91 213221 317 2.95 24841 1.44 221222 405 3.76 30557 1.77 222223 372 3.46 21264 1.23 223231 211 1.96 35210 2.04 231232 295 2.74 61152 3.54 232233 292 2.71 61347 3.55 233311 489 4.54 106768 6.18 311312 645 5.99 128713 7.45 312313 463 4.30 79917 4.62 313321 360 3.34 20088 1.16 321322 420 3.90 27167 1.57 322323 401 3.73 20265 1.17 323

05/18/23 106


331 249 2.31 40768 2.36 331332 355 3.30 81419 4.71 332333 419 3.89 87266 5.05 333

C00001 - Are you adult responsible for child


A 2 0.02 406 0.02 Mult response. 166 1.54 25901 1.50 No response1 10506 97.60 1688136 97.67 Yes2 90 0.84 13964 0.81 No

C00002 - Which hlth plan did you use most


. 103 0.96 16597 0.96 Did not answerN 170 1.58 32839 1.90 Did not use any health

plan in lst 12 moA 134 1.24 22661 1.31 Invalid multiple responsesD 77 0.72 13696 0.79 Not sure1 7507 69.74 1124469 65.06 TRICARE Prime3 1324 12.30 261024 15.10 TRICARE Extra or

Standard5 95 0.88 18715 1.08 Federal Employees

Health Benefit Program6 81 0.75 15282 0.88 Medicaid7 351 3.26 69361 4.01 A Civilian HMO8 712 6.61 139886 8.09 Other civilian health

insurance9 210 1.95 13877 0.80 Uniformed Services

Family Health Plan

C00003 - In last 12 mos,# mos in a row cvrd w/Pln


A 14 0.13 1969 0.11 Mult responseN 218 2.03 40311 2.33 No health plan. 189 1.76 31542 1.82 No response2 119 1.11 21260 1.23 Less than 2 mos3 312 2.90 53070 3.07 2-6 months4 9912 92.08 1580257 91.43 7-12 months

05/18/23 107


C00004A - Child covered by TRICARE Prime


1 7764 72.13 1163747 67.33 Marked2 3000 27.87 564660 32.67 Not marked

C00004B - Child covered by TRICARE Extra/Standard



C00004C - Child covered by Fed. EMP Health Benefit



C00004D - Child covered by Medicaid



C00004E - Child covered by Civilian HMO



C00004F - Child covered by Other Civilian Ins.

Unweighted Weighted

05/18/23 108




C00004G - Child covered by USFP



C00004H - Not sure who Child covered by



C00004I - Child did not use health plan last 12mos



C00005 - Does child have personal Dr/Nurse


. 74 0.69 13622 0.79 No response1 7487 69.56 1121279 64.87 Yes2 3203 29.76 593506 34.34 No

C00006 - How much prblem to get personal Dr/Nurse


A 6 0.06 1126 0.07 Mult responseN 3098 28.78 570720 33.02 No prsnl Dr/Nrs

05/18/23 109


. 537 4.99 85780 4.96 No responseC 281 2.61 51227 2.96 Should be skipped1 639 5.94 87591 5.07 A big problem2 1300 12.08 186448 10.79 A small problem3 4903 45.55 745514 43.13 Not a problem

C00007 - Talk about feeling/growing/behaving


A 13 0.12 2118 0.12 Mult responseN 3209 29.81 590856 34.18 No prsnl Dr/Nrs. 546 5.07 86046 4.98 No responseC 210 1.95 38124 2.21 Should be skipped1 614 5.70 88172 5.10 Never2 1095 10.17 158360 9.16 Sometimes3 1577 14.65 237790 13.76 Usually4 3500 32.52 526941 30.49 Always

C00008 - Rating of childs personal Dr/Nurse


A 22 0.20 3905 0.23 Mult responseN 3187 29.61 586855 33.95 No prsnl Dr. 515 4.78 80618 4.66 No responseC 222 2.06 40160 2.32 Should be skipped0 31 0.29 4000 0.23 0 Worst Prsn Dr1 30 0.28 3657 0.21 12 56 0.52 6758 0.39 23 93 0.86 13053 0.76 34 117 1.09 15653 0.91 45 413 3.84 59959 3.47 56 342 3.18 49375 2.86 67 899 8.35 130943 7.58 78 1582 14.70 242633 14.04 89 1261 11.71 189939 10.99 910 1994 18.52 300901 17.41 10 Best Prsn Dr

C00009 - Does child have primary care manager


D 1286 11.95 230177 13.32 I don't knowN 1332 12.37 251733 14.56 No TRICARE Prime. 352 3.27 61360 3.55 No response1 6296 58.49 901420 52.15 Yes

05/18/23 110


2 1498 13.92 283718 16.42 No

C00010 - Know name of childs Primary care mgr


A 3 0.03 623 0.04 Mult response. 454 4.22 76427 4.42 No responseN 4116 38.24 765628 44.30 Valid skip1 4855 45.10 644611 37.30 Yes2 1336 12.41 241118 13.95 No

C00011 - In last 12 mos how much prblm to see PCM


A 5 0.05 939 0.05 Mult responseN 4308 40.02 799590 46.26 No prmry care mgr. 614 5.70 104165 6.03 No responseC 26 0.24 4377 0.25 Should be skipped1 461 4.28 74338 4.30 A big problem2 1256 11.67 199536 11.54 A small problem3 4094 38.03 545462 31.56 Not a problem

05/18/23 111


C00012 - Is primary care mgr military or civilian


A 13 0.12 1819 0.11 Mult responseN 4233 39.33 787097 45.54 No TRICARE Mgr. 544 5.05 89679 5.19 No responseD 111 1.03 18690 1.08 Not sureC 120 1.11 20405 1.18 Should be skipped1 3091 28.72 603822 34.94 Mil trtmnt fclty2 2652 24.64 206895 11.97 Civ trtmnt fclty

C00013 - Did you think child needed to see spclst



C00014 - How much prblm to get referral to spclst


N 6270 58.25 1015304 58.74 Didn't see spclstA 16 0.15 2456 0.14 Mult response. 254 2.36 40836 2.36 No responseC 944 8.77 150306 8.70 Should be skipped1 494 4.59 74994 4.34 A big problem2 613 5.69 91699 5.31 A small problem3 2173 20.19 352811 20.41 Not a problem

C00015 - In last 12 mos did child see specialist


. 217 2.02 34646 2.00 No responseC 933 8.67 147845 8.55 Should be skippedN 6205 57.65 1007269 58.28 Valid skip1 2977 27.66 471744 27.29 Yes2 432 4.01 66904 3.87 No

05/18/23 112


C00016 - Rating of specialist seen most often

05/18/23 113



A 12 0.11 1864 0.11 Mult response. 315 2.93 49891 2.89 No responseN 7365 68.42 1188334 68.75 No specialistC 305 2.83 47749 2.76 Should be skipped0 34 0.32 5232 0.30 0 Worst spclst1 17 0.16 2161 0.13 12 27 0.25 3582 0.21 23 39 0.36 5524 0.32 34 50 0.46 7041 0.41 45 166 1.54 25837 1.49 56 150 1.39 23813 1.38 67 334 3.10 54449 3.15 78 581 5.40 95576 5.53 89 557 5.17 87909 5.09 910 812 7.54 129445 7.49 10 Best spclst

C00017 - Specialist same as personal Dr


A 10 0.09 1726 0.10 Mult responseN 7246 67.32 1170883 67.74 No dr/specialist. 293 2.72 46196 2.67 No responseC 373 3.47 60680 3.51 Should be skipped1 339 3.15 54265 3.14 Yes2 2503 23.25 394657 22.83 No

C00018 - Call during reg. Hrs to get help/advice



05/18/23 114


C00019 - Called during reg Hrs did you get hlp


A 12 0.11 1772 0.10 Mult responseN 3953 36.72 663588 38.39 No call hlp/advc. 395 3.67 62747 3.63 No responseC 399 3.71 66200 3.83 Should be skipped1 170 1.58 28087 1.63 Never2 870 8.08 144123 8.34 Sometimes3 1375 12.77 220937 12.78 Usually4 3590 33.35 540953 31.30 Always

C00020 - Make appt for regular/routine hlthcre



C00021 - How oftn get appt for care soon as wnted


A 14 0.13 2090 0.12 Mult responseN 2194 20.38 364284 21.08 No appointment. 431 4.00 67715 3.92 No responseC 271 2.52 45484 2.63 Should be skipped1 372 3.46 60231 3.48 Never2 1287 11.96 218353 12.63 Sometimes3 2421 22.49 403218 23.33 Usually4 3774 35.06 567031 32.81 Always

05/18/23 115


C00022 - Wait btwn mking appt and seeing provider


A 45 0.42 6164 0.36 Mult responseN 2243 20.84 373220 21.59 No appointments. 2063 19.17 329040 19.04 No responseC 256 2.38 43203 2.50 Should be skipped1 1596 14.83 238210 13.78 Same day2 1969 18.29 311300 18.01 1 day3 1166 10.83 189518 10.96 2-3 days4 885 8.22 145203 8.40 4-7 days5 292 2.71 51052 2.95 8-14 days6 199 1.85 33924 1.96 15-30 days7 50 0.46 7572 0.44 31 days or lnger

C00023 - Have illness/injury need care right away



C00024 - Get needed care as soon as wanted


N 4568 42.44 744103 43.05 Didn't need careA 9 0.08 1484 0.09 Mult response. 618 5.74 97245 5.63 No responseC 283 2.63 44268 2.56 Should be skipped1 265 2.46 44827 2.59 Never2 602 5.59 101374 5.87 Sometimes3 1200 11.15 195912 11.33 Usually4 3219 29.91 499193 28.88 Always

05/18/23 116


C00025 - Wait btwn trying to & seeing provider


N 4303 39.98 700211 40.51 Didn't need careA 93 0.86 13854 0.80 Mult response. 274 2.55 43612 2.52 No responseC 379 3.52 60141 3.48 Should be skipped1 3143 29.20 496386 28.72 Same day2 1135 10.54 179935 10.41 1 day3 856 7.95 139348 8.06 2-3 days4 343 3.19 56689 3.28 4-7 days5 154 1.43 25075 1.45 8-14 days6 84 0.78 13157 0.76 15 days or lnger

C00026 - Appointment for well-patient care



C00027 - Get appt for well-patient care


N 3795 35.26 621464 35.96 Didn't need apptA 10 0.09 1603 0.09 Mult response. 337 3.13 53757 3.11 No responseC 279 2.59 46721 2.70 Should be skipped1 507 4.71 82946 4.80 Never2 991 9.21 165290 9.56 Sometimes3 2393 22.23 387598 22.43 Usually4 2452 22.78 369028 21.35 Always

05/18/23 117


C00028 - Wait to see provider for well-patnt care


N 3851 35.78 629057 36.40 Didn't need apptA 14 0.13 2000 0.12 Mult response. 332 3.08 52860 3.06 No responseC 276 2.56 46323 2.68 Should be skipped1 3476 32.29 528816 30.60 Within 7 days2 1542 14.33 261287 15.12 8-14 days3 892 8.29 150362 8.70 15-28 days4 381 3.54 57702 3.34 >28 days

C00029 - Times to ER


A 15 0.14 2017 0.12 Mult response. 117 1.09 18887 1.09 No response1 7366 68.43 1169768 67.68 None2 2052 19.06 335575 19.42 13 1042 9.68 172239 9.97 2-34 145 1.35 25094 1.45 4-65 27 0.25 4826 0.28 More than 6

C00030 - Times to Dr office/Clinic (excluding ER)


A 35 0.33 5767 0.33 Mult response. 84 0.78 13505 0.78 No response1 1219 11.32 206221 11.93 None2 1444 13.42 236245 13.67 13 2115 19.65 342470 19.81 24 1986 18.45 320498 18.54 35 1513 14.06 241724 13.99 46 1808 16.80 274904 15.91 5-97 560 5.20 87073 5.04 10 or more

05/18/23 118


C00031 - Problem to get necessary care


A 8 0.07 1515 0.09 Mult response. 139 1.29 23088 1.34 No responseN 1114 10.35 188432 10.90 No visitsC 97 0.90 16116 0.93 Should be skipped1 432 4.01 68935 3.99 A big problem2 1421 13.20 224317 12.98 A small problem3 7553 70.17 1206003 69.78 Not a problem

C00032 - Problem wait for approval


A 5 0.05 832 0.05 Mult response. 178 1.65 29807 1.72 No responseN 1164 10.81 195749 11.33 No visitsC 94 0.87 15568 0.90 Should be skipped1 478 4.44 65004 3.76 A big problem2 1067 9.91 154621 8.95 A small problem3 7778 72.26 1266827 73.29 Not a problem

C00033 - How oftn wait >15 mins


D 492 4.57 81544 4.72 I don't knowA 18 0.17 2134 0.12 Mult response. 134 1.24 22405 1.30 No responseN 1086 10.09 183913 10.64 No visitsC 94 0.87 15585 0.90 Should be skipped1 2077 19.30 336167 19.45 Never2 3717 34.53 594189 34.38 Sometimes3 1665 15.47 267018 15.45 Usually4 1481 13.76 225454 13.04 Always

05/18/23 119


C00034 - How oftn staff treat w/courtesy &respect



C00035 - How oftn were staff helpful



C00036 - How oftn did staff listen carefully



05/18/23 120


C00037 - How oftn did staff explain things to you



C00038 - How oftn staff respect what had to say



C00039 - Child old enough to talk to Dr



05/18/23 121


C00040 - Dr explain in way for child to undrstnd


D 182 1.69 30217 1.75 I don't knowA 8 0.07 1047 0.06 Mult response. 376 3.49 60011 3.47 No responseN 3685 34.23 596943 34.54 No visit/too yngC 150 1.39 25214 1.46 Should be skipped1 223 2.07 36176 2.09 Never2 786 7.30 132179 7.65 Sometimes3 2032 18.88 332100 19.21 Usually4 3322 30.86 514521 29.77 Always

C00041 - How oftn spend enough time w/child



05/18/23 122


C00042 - Rating of childs healthcare


A 32 0.30 5411 0.31 Mult response. 158 1.47 25998 1.50 No responseN 1062 9.87 180536 10.45 No visitsC 96 0.89 15760 0.91 Should be skipped0 40 0.37 6616 0.38 0 Worst care1 56 0.52 8852 0.51 12 77 0.72 11523 0.67 23 192 1.78 30383 1.76 34 238 2.21 37758 2.18 45 637 5.92 102383 5.92 56 582 5.41 93631 5.42 67 1356 12.60 222823 12.89 78 2284 21.22 375193 21.71 89 1979 18.39 310146 17.94 910 1975 18.35 301395 17.44 10 Best care

C00043 - Type of facility child used most often


A 33 0.31 5171 0.30 Mult response. 188 1.75 29395 1.70 No responseN 715 6.64 118850 6.88 None1 4341 40.33 862026 49.87 Mil facility2 5290 49.15 697648 40.36 Civ facility3 197 1.83 15317 0.89 Uniformed Services

C00044 - Send in any claims


N 953 8.85 166702 9.64 I don't know. 143 1.33 22980 1.33 No response1 5561 51.66 802515 46.43 Yes2 4107 38.15 736209 42.59 No

05/18/23 123


C00045 - Handle claim in reasonable time


D 623 5.79 86608 5.01 I don't knowA 11 0.10 1574 0.09 Mult responseN 4904 45.56 873190 50.52 No claims sent. 264 2.45 40710 2.36 No responseC 167 1.55 31821 1.84 Should be skipped1 350 3.25 51686 2.99 Never2 743 6.90 106797 6.18 Sometimes3 1904 17.69 281369 16.28 Usually4 1798 16.70 254651 14.73 Always

C00046 - Handle claim correctly



C00047 - Plan make clear how much to pay



05/18/23 124


C00048 - Look for info/written material



C00049 - Find/understand info in written material


N 6566 61.00 1101006 63.70 Didn't look infoA 4 0.04 563 0.03 Mult response. 257 2.39 39702 2.30 No responseC 293 2.72 50379 2.91 Should be skipped1 580 5.39 88990 5.15 A big problem2 1323 12.29 192015 11.11 A small problem3 1741 16.17 255752 14.80 Not a problem

C00050 - Call customer service to get info



C00051 - Problem get help when call customer svc


N 6257 58.13 1050895 60.80 Didn't call CSA 11 0.10 1309 0.08 Mult response. 242 2.25 38242 2.21 No responseC 420 3.90 73642 4.26 Should be skipped1 812 7.54 114065 6.60 A big problem2 1190 11.06 172284 9.97 A small problem3 1832 17.02 277970 16.08 Not a problem

C00052 - Called/written plan with complaint

05/18/23 125




C00053 - How long to resolve complaint


A 11 0.10 1525 0.09 Mult responseN 8352 77.59 1377486 79.70 No call/write. 201 1.87 30242 1.75 No responseC 534 4.96 88343 5.11 Should be skipped1 292 2.71 41911 2.42 Same day2 158 1.47 22423 1.30 1 week3 124 1.15 16693 0.97 2 weeks4 89 0.83 13858 0.80 3 weeks5 389 3.61 52138 3.02 4 or more weeks6 614 5.70 83788 4.85 Still waiting

C00054 - Complaint/problem settled to satisfction


A 14 0.13 2088 0.12 Mult responseN 8827 82.00 1449542 83.87 No call/write. 194 1.80 29661 1.72 No responseC 442 4.11 68696 3.97 Should be skipped1 819 7.61 113103 6.54 Yes2 243 2.26 34743 2.01 No3 225 2.09 30573 1.77 Still waiting

C00055 - Experience with paperwork



C00056 - Problem with paperwork

Unweighted Weighted

05/18/23 126



A 16 0.15 2302 0.13 Mult responseN 6949 64.56 1137995 65.84 No experience. 206 1.91 31923 1.85 No responseC 417 3.87 68534 3.97 Should be skipped1 624 5.80 91625 5.30 A big problem2 1087 10.10 165354 9.57 A small problem3 1465 13.61 230675 13.35 Not a problem

C00057 - Rating of exprience with child hlth plan


A 24 0.22 2789 0.16 Mult response. 322 2.99 53436 3.09 No response0 184 1.71 28313 1.64 0 Worst plan1 131 1.22 18896 1.09 12 232 2.16 36918 2.14 23 306 2.84 45527 2.63 34 346 3.21 54571 3.16 45 1241 11.53 201021 11.63 56 882 8.19 140555 8.13 67 1624 15.09 265034 15.33 78 2236 20.77 368444 21.32 89 1735 16.12 277076 16.03 910 1501 13.94 235827 13.64 10 Best plan

C00058 - Rate child overall health


A 22 0.20 3788 0.22 Mult response. 180 1.67 29161 1.69 No response1 39 0.36 5941 0.34 Poor2 225 2.09 36127 2.09 Fair3 1240 11.52 200188 11.58 Good4 3987 37.04 636024 36.80 Very good5 5071 47.11 817178 47.28 Excellent

05/18/23 127


C00059 - Child use medicine prescribed by Dr



C00060 - Medicine b/c medical,behavioral,other



C00061 - Medicine b/c cndtn expected last>=12 mos


A 4 0.04 429 0.02 Mult response. 140 1.30 20740 1.20 No responseC 150 1.39 25099 1.45 Should be skippedN 7973 74.07 1283247 74.24 Valid skip1 2110 19.60 337762 19.54 Yes2 387 3.60 61131 3.54 No

C00062 - Mre medical,mntl,edcution svcs thn usual



05/18/23 128


C00063 - Use svcs b/c medical, behavioral, oth



C00064 - Svcs b/c condition expected last>=12 mos



C00065 - Limited/prevented in ability



C00066 - Limited b/c medical, behavioral, other



C00067 - Limited b/c condition expected last>=1yr

Unweighted Weighted

05/18/23 129




C00068 - Get special therapy



C00069 - Therapy b/c medical, behavioral, other



C00070 - Therapy b/c condition expected last>=1yr



C00071 - Problem for which gets trtmnt/counseling


. 90 0.84 13678 0.79 No response

05/18/23 130


1 1569 14.58 256063 14.81 Yes2 9105 84.59 1458665 84.39 No

C00072 - Trtmnt/counseling b/c conditn last>=1yr


A 2 0.02 270 0.02 Mult response. 132 1.23 20823 1.20 No responseN 9105 84.59 1458665 84.39 Valid skip1 808 7.51 131777 7.62 Yes2 717 6.66 116872 6.76 No

C00073 - Last time routine preventive care appt


A 18 0.17 2960 0.17 Mult responseN 98 0.91 16900 0.98 Never had exam. 143 1.33 21525 1.25 No response1 6391 59.37 1007341 58.28 < 12 Months2 2753 25.58 450595 26.07 1-2 years3 1005 9.34 168201 9.73 GT 2 LT 5 years4 356 3.31 60884 3.52 5+ Years

C00074 - Childs age now


1 269 2.50 44651 2.58 Less than 1 year2 1309 12.16 201271 11.64 1-2 years3 1682 15.63 266701 15.43 3-5 years4 1533 14.24 260122 15.05 6-8 years5 2339 21.73 400343 23.16 9-12 years6 3632 33.74 555320 32.13 13-17 years

C00075 - Child recd all immunizations


N 5948 55.26 967638 55.98 I don't knowA 1 0.01 239 0.01 Mult response. 140 1.30 20167 1.17 No responseC 3519 32.69 561228 32.47 Should be skipped

05/18/23 131


1 1103 10.25 170564 9.87 Yes2 53 0.49 8572 0.50 No

C00076A - # times child recd Dtap,DT,DTP


D 176 1.64 26758 1.55 Don't knowA 11 0.10 2220 0.13 Mult response. 276 2.56 40600 2.35 No responseC 3162 29.38 506791 29.32 Should be skippedN 6293 58.46 1020345 59.03 Valid skip1 7 0.07 1070 0.06 02 44 0.41 6718 0.39 13 73 0.68 10981 0.64 24 237 2.20 37076 2.15 35 446 4.14 70283 4.07 46 39 0.36 5565 0.32 5 or more

C00076B - # times child recd MMR



05/18/23 132


C00076C - # times child recd IPV or OPV



C00076D - # times child recd Hib



05/18/23 133


C00076E - # times child recd HepB



C00076F - # times child recd Varicella



C00077A - Talk about growth/development


C 9186 85.34 1482485 85.77 Should be skipped1 1228 11.41 192672 11.15 Marked2 350 3.25 53249 3.08 Not marked

05/18/23 134


C00077B - Talk about behaviors to expect



C00077C - Talk about dress/bathe/feed child



C00077D - Talk about help child grow/learn



C00077E - Talk about tlking/reading/plying w/child



05/18/23 135


C00077F - Talk about keep child from injured



C00077G - Talk about make house safe



C00077H - Talk about make car safe



C00078 - Is child male or female


A 54 0.50 7981 0.46 Mult response. 85 0.79 12500 0.72 No response1 5456 50.69 882893 51.08 Male2 5169 48.02 825033 47.73 Female

05/18/23 136


C00079 - Is child Hispanic/Latino


A 8 0.07 1623 0.09 Mult response. 443 4.12 69349 4.01 No response1 1180 10.96 187866 10.87 Hispanic/Latino2 9133 84.85 1469569 85.02 Not Hspnc/Latino

C00080A - Child race:white



C00080B - Child race:Black



C00080C - Child race:Asian



C00080D - Child race:Native Hawaiian/Pacific Islnd



C00080E - Child race:Am. Indian/Alaskan

05/18/23 137




C00081 - Your age now


A 37 0.34 4660 0.27 Mult response. 116 1.08 17027 0.99 No response1 573 5.32 88270 5.11 Under 182 390 3.62 64340 3.72 18 to 243 2612 24.27 427279 24.72 25 to 344 4759 44.21 761656 44.07 35 to 445 1860 17.28 294873 17.06 45 to 546 317 2.95 53023 3.07 55 to 647 88 0.82 15167 0.88 65 to 748 12 0.11 2113 0.12 75 or older

C00082 - Are you male or female


A 8 0.07 1247 0.07 Mult response. 110 1.02 17255 1.00 No response1 3153 29.29 512504 29.65 Male2 7493 69.61 1197401 69.28 Female

05/18/23 138


C00083 - highest grade/level you completed


A 92 0.85 14345 0.83 Mult response. 122 1.13 18869 1.09 No response1 36 0.33 5535 0.32 8th or less2 141 1.31 23447 1.36 No diploma3 1853 17.21 296048 17.13 Diploma/GED4 4859 45.14 774941 44.84 Some College/AA5 1807 16.79 287907 16.66 4-yr college deg6 1854 17.22 307316 17.78 >4-yr college deg

C00084 - How related to child


A 78 0.72 13652 0.79 Mult response. 65 0.60 10164 0.59 No response1 10394 96.56 1669125 96.57 Mother or father2 88 0.82 12977 0.75 Grandparent3 6 0.06 1021 0.06 Aunt or uncle6 65 0.60 10325 0.60 Legal guardian7 68 0.63 11143 0.64 Other

FLAG_FIN - Final Disposition


1 10764 100.00 1728407 100.00 Returned survey

DUPFLAG - Multiple Response Indicator


NO 10727 99.66 1722227 99.64 NOYES 37 0.34 6180 0.36 YES

05/18/23 139


N2 - Coding Scheme Note 2


1 7132 66.26 1061220 61.40 12 61 0.57 10845 0.63 23 355 3.30 60059 3.47 34 3139 29.16 582008 33.67 45 74 0.69 13622 0.79 56 3 0.03 653 0.04 6



1 3259 30.28 603340 34.91 12 6944 64.51 1037101 60.00 23 120 1.11 18607 1.08 35 441 4.10 69359 4.01 5



1 3389 31.48 623912 36.10 12 7345 68.24 1099427 63.61 23 30 0.28 5068 0.29 3



1 23 0.21 2846 0.16 12 5790 53.79 812910 47.03 23 4 0.04 782 0.05 34 4040 37.53 750955 43.45 45 483 4.49 85664 4.96 56 28 0.26 4878 0.28 67 44 0.41 9013 0.52 78 352 3.27 61360 3.55 8

05/18/23 140




1 4148 38.54 771366 44.63 12 6430 59.74 924440 53.49 23 186 1.73 32601 1.89 3



1 3073 28.55 489453 28.32 12 102 0.95 16589 0.96 23 403 3.74 60444 3.50 34 7032 65.33 1137942 65.84 45 150 1.39 23397 1.35 56 4 0.04 583 0.03 6

N8 - Coding scheme Note 8


1 7138 66.31 1155113 66.83 12 2758 25.62 438167 25.35 23 4 0.04 675 0.04 34 219 2.03 33577 1.94 45 427 3.97 66161 3.83 56 217 2.02 34646 2.00 67 1 0.01 68 0.00 7

N9 - Coding scheme Note 9


1 6049 56.20 943685 54.60 12 28 0.26 4834 0.28 23 221 2.05 33343 1.93 34 4324 40.17 724954 41.94 45 142 1.32 21591 1.25 5


05/18/23 141



1 7970 74.04 1269158 73.43 12 31 0.29 5013 0.29 23 215 2.00 31964 1.85 34 2398 22.28 399297 23.10 45 145 1.35 22033 1.27 56 5 0.05 942 0.05 6



1 5070 47.10 807726 46.73 12 22 0.20 3407 0.20 23 1015 9.43 160345 9.28 34 4619 42.91 751268 43.47 45 37 0.34 5619 0.33 56 1 0.01 42 0.00 6



1 6481 60.21 1025453 59.33 12 52 0.48 8981 0.52 23 149 1.38 24528 1.42 34 4010 37.25 656905 38.01 45 71 0.66 12292 0.71 56 1 0.01 247 0.01 6

05/18/23 142




1 1116 10.37 188428 10.90 12 165 1.53 27198 1.57 23 9426 87.57 1502914 86.95 34 15 0.14 2816 0.16 45 39 0.36 6583 0.38 56 3 0.03 468 0.03 6



1 1134 10.54 191712 11.09 12 266 2.47 41144 2.38 23 31 0.29 5537 0.32 34 6381 59.28 1018667 58.94 45 1 0.01 168 0.01 56 172 1.60 27573 1.60 67 2666 24.77 424231 24.54 78 110 1.02 18867 1.09 89 3 0.03 509 0.03 9



1 5219 48.49 746977 43.22 12 14 0.13 2748 0.16 23 4 0.04 835 0.05 34 342 3.18 55538 3.21 45 4899 45.51 872239 50.46 56 137 1.27 25904 1.50 67 143 1.33 22980 1.33 78 6 0.06 1186 0.07 8

05/18/23 143




1 3539 32.88 519256 30.04 12 20 0.19 3758 0.22 23 188 1.75 30540 1.77 34 6833 63.48 1146643 66.34 45 178 1.65 27225 1.58 56 6 0.06 985 0.06 6



1 3697 34.35 542301 31.38 12 26 0.24 4327 0.25 23 220 2.04 34270 1.98 34 6649 61.77 1119815 64.79 45 170 1.58 27300 1.58 56 2 0.02 395 0.02 6



1 1606 14.92 221624 12.82 12 19 0.18 2970 0.17 23 131 1.22 19009 1.10 34 8854 82.26 1460789 84.52 45 152 1.41 23795 1.38 56 2 0.02 220 0.01 6

05/18/23 144




1 8875 82.45 1463979 84.70 12 1259 11.70 177746 10.28 23 387 3.60 52831 3.06 34 225 2.09 30573 1.77 45 7 0.07 1428 0.08 56 11 0.10 1850 0.11 6



1 2827 26.26 432542 25.03 12 27 0.25 4248 0.25 23 409 3.80 63645 3.68 34 7337 68.16 1202179 69.55 45 162 1.51 25692 1.49 56 2 0.02 101 0.01 6



1 40 0.37 5641 0.33 12 2722 25.29 435775 25.21 23 11 0.10 1440 0.08 34 7923 73.61 1275800 73.81 45 64 0.59 9417 0.54 56 4 0.04 335 0.02 6

05/18/23 145




1 7927 73.64 1276135 73.83 12 2505 23.27 399667 23.12 23 194 1.80 31919 1.85 34 29 0.27 5123 0.30 45 3 0.03 214 0.01 56 104 0.97 15057 0.87 67 2 0.02 291 0.02 7



1 29 0.27 4377 0.25 12 1455 13.52 236678 13.69 23 44 0.41 7017 0.41 34 9146 84.97 1466720 84.86 45 87 0.81 13300 0.77 56 3 0.03 314 0.02 6



1 9149 85.00 1467034 84.88 12 1396 12.97 226932 13.13 23 76 0.71 12221 0.71 34 23 0.21 3864 0.22 45 3 0.03 439 0.03 56 116 1.08 17678 1.02 67 1 0.01 239 0.01 7

05/18/23 146




1 56 0.52 8835 0.51 12 697 6.48 113616 6.57 23 24 0.22 3400 0.20 34 9900 91.97 1590322 92.01 45 83 0.77 11910 0.69 56 4 0.04 324 0.02 6



1 9904 92.01 1590646 92.03 12 700 6.50 113996 6.60 23 37 0.34 5639 0.33 34 21 0.20 3021 0.17 46 102 0.95 15106 0.87 6



1 20 0.19 2782 0.16 12 713 6.62 117532 6.80 23 36 0.33 5558 0.32 34 9915 92.11 1591547 92.08 45 77 0.72 10520 0.61 56 3 0.03 468 0.03 6

05/18/23 147




1 9918 92.14 1592014 92.11 12 565 5.25 92464 5.35 23 152 1.41 25874 1.50 34 31 0.29 4676 0.27 45 1 0.01 76 0.00 56 97 0.90 13302 0.77 6



1 1035 9.62 168173 9.73 12 9103 84.57 1458185 84.37 23 534 4.96 87891 5.09 34 90 0.84 13678 0.79 45 2 0.02 480 0.03 5



1 269 2.50 44651 2.58 12 1034 9.61 161634 9.35 23 9186 85.34 1482485 85.77 34 141 1.31 20046 1.16 45 134 1.24 19591 1.13 5

MISS_1 - Count of: Violates Skip Pattern


0 10764 100.00 1728407 100.00 0 times

05/18/23 148


MISS_4 - Count of: Incomplete grid error


0 10764 100.00 1728407 100.00 0 times

MISS_5 - Count of: Dont know or not sure


0 6927 64.35 1099716 63.63 0 times1 2443 22.70 406481 23.52 1 time2 774 7.19 123166 7.13 2 times3 277 2.57 44453 2.57 3 times4 116 1.08 18377 1.06 4 times5 53 0.49 8147 0.47 5 times6 109 1.01 16970 0.98 6 times7 40 0.37 6933 0.40 7 times8 11 0.10 1743 0.10 8 times9 9 0.08 1465 0.08 9 times10 2 0.02 425 0.02 10 times11 1 0.01 167 0.01 11 times12 2 0.02 363 0.02 12 times

05/18/23 149


MISS_6 - Count of: Not applicable - valid skip


0 5310 49.33 804140 46.52 0 times1 2903 26.97 492799 28.51 1 time2 1104 10.26 185995 10.76 2 times3 544 5.05 90741 5.25 3 times4 281 2.61 48361 2.80 4 times5 179 1.66 30217 1.75 5 times6 112 1.04 17995 1.04 6 times7 52 0.48 8810 0.51 7 times8 56 0.52 10463 0.61 8 times9 32 0.30 5498 0.32 9 times10 23 0.21 3847 0.22 10 times11 23 0.21 3909 0.23 11 times12 25 0.23 4293 0.25 12 times13 28 0.26 4984 0.29 13 times14 22 0.20 3621 0.21 14 times15 12 0.11 2063 0.12 15 times16 14 0.13 2743 0.16 16 times17 5 0.05 826 0.05 17 times18 4 0.04 705 0.04 18 times19 5 0.05 940 0.05 19 times20 4 0.04 873 0.05 20 times21 4 0.04 839 0.05 21 times22 1 0.01 233 0.01 22 times23 4 0.04 582 0.03 23 times24 2 0.02 400 0.02 24 times25 2 0.02 267 0.02 25 times26 1 0.01 234 0.01 26 times27 1 0.01 197 0.01 27 times28 1 0.01 52 0.00 28 times29 2 0.02 292 0.02 29 times30 1 0.01 166 0.01 30 times32 1 0.01 52 0.00 32 times33 1 0.01 197 0.01 33 times34 1 0.01 206 0.01 34 times36 3 0.03 639 0.04 36 times40 1 0.01 228 0.01 40 or more times

05/18/23 150


MISS_7 - Count of: Out-of-range error


0 10764 100.00 1728407 100.00 0 times

MISS_8 - Count of: Multiple response error


0 9611 89.29 1545410 89.41 0 times1 927 8.61 148299 8.58 1 time2 151 1.40 23700 1.37 2 times3 42 0.39 6528 0.38 3 times4 16 0.15 1755 0.10 4 times5 4 0.04 677 0.04 5 times6 7 0.07 1326 0.08 6 times7 1 0.01 58 0.00 7 times9 2 0.02 311 0.02 9 times10 1 0.01 64 0.00 10 times14 1 0.01 233 0.01 14 times18 1 0.01 46 0.00 18 times

05/18/23 151


MISS_9 - Count of: No response - invalid skip


0 18 0.17 2695 0.16 0 times1 20 0.19 2683 0.16 1 time2 24 0.22 3852 0.22 2 times3 26 0.24 4382 0.25 3 times4 43 0.40 5082 0.29 4 times5 37 0.34 5080 0.29 5 times6 52 0.48 7399 0.43 6 times7 69 0.64 10851 0.63 7 times8 93 0.86 13360 0.77 8 times9 122 1.13 17738 1.03 9 times10 130 1.21 17574 1.02 10 times11 175 1.63 25370 1.47 11 times12 186 1.73 24620 1.42 12 times13 217 2.02 29990 1.74 13 times14 272 2.53 38424 2.22 14 times15 306 2.84 42924 2.48 15 times16 363 3.37 51059 2.95 16 times17 405 3.76 56677 3.28 17 times18 466 4.33 68600 3.97 18 times19 514 4.78 75222 4.35 19 times20 510 4.74 77418 4.48 20 times21 549 5.10 83856 4.85 21 times22 564 5.24 90185 5.22 22 times23 554 5.15 89852 5.20 23 times24 571 5.30 96862 5.60 24 times25 563 5.23 96427 5.58 25 times26 528 4.91 91653 5.30 26 times27 419 3.89 74328 4.30 27 times28 373 3.47 67794 3.92 28 times29 327 3.04 61092 3.53 29 times30 296 2.75 51965 3.01 30 times31 244 2.27 43826 2.54 31 times32 216 2.01 39063 2.26 32 times33 163 1.51 29679 1.72 33 times34 123 1.14 22653 1.31 34 times35 79 0.73 13913 0.80 35 times36 82 0.76 13088 0.76 36 times37 76 0.71 12532 0.73 37 times38 57 0.53 8894 0.51 38 times39 64 0.59 10484 0.61 39 times

40 -- 72 868 8.06 149264 8.64 40 or more times

05/18/23 152


MISS_TOT - Total number of missing responses


0 2 0.02 241 0.01 0 times1 4 0.04 398 0.02 1 time2 4 0.04 701 0.04 2 times3 9 0.08 1147 0.07 3 times4 22 0.20 2690 0.16 4 times5 24 0.22 3068 0.18 5 times6 34 0.32 4425 0.26 6 times7 52 0.48 6341 0.37 7 times8 47 0.44 7849 0.45 8 times9 83 0.77 10885 0.63 9 times10 111 1.03 14327 0.83 10 times11 127 1.18 19524 1.13 11 times12 164 1.52 22688 1.31 12 times13 185 1.72 24412 1.41 13 times14 196 1.82 26721 1.55 14 times15 235 2.18 31327 1.81 15 times16 258 2.40 35153 2.03 16 times17 344 3.20 48555 2.81 17 times18 367 3.41 52011 3.01 18 times19 429 3.99 62373 3.61 19 times20 489 4.54 70258 4.06 20 times21 475 4.41 71064 4.11 21 times22 526 4.89 80849 4.68 22 times23 578 5.37 88621 5.13 23 times24 583 5.42 95516 5.53 24 times25 545 5.06 90645 5.24 25 times26 587 5.45 100968 5.84 26 times27 501 4.65 90513 5.24 27 times28 471 4.38 82454 4.77 28 times29 392 3.64 68643 3.97 29 times30 346 3.21 62069 3.59 30 times31 276 2.56 48970 2.83 31 times32 266 2.47 48517 2.81 32 times33 211 1.96 39639 2.29 33 times34 192 1.78 33880 1.96 34 times35 130 1.21 22621 1.31 35 times36 128 1.19 23935 1.38 36 times37 85 0.79 15713 0.91 37 times38 79 0.73 13326 0.77 38 times39 69 0.64 11759 0.68 39 times

40 -- 72 1138 10.57 193612 11.20 40 or more times

05/18/23 153


CONUS - CONUS - CONUS/OCONUS Indicator


1 10764 100.00 1728407 100.00 In CONUS

XENRLLMT - Enrollment in TRICARE Prime


1 7749 71.99 1114564 64.49 Enrolled2 3015 28.01 613843 35.51 Not enrolled

XENR_PCM - Enrollment by PCM type


1 4398 40.86 908829 52.58 Enrolled - Mil PCM2 3351 31.13 205736 11.90 Enrolled - Civ PCM3 3015 28.01 613843 35.51 Not Enrolled

XINS_COV - Insurance Coverage


. 484 4.50 85793 4.96 Missing/Unknown1 7507 69.74 1124469 65.06 Prime2 1324 12.30 261024 15.10 Standard/Extra3 1449 13.46 257121 14.88 Other Insurance

05/18/23 154


XBNFGRP - Constructed Beneficiary Group


1 8 0.07 1634 0.09 Active Duty2 6542 60.78 1069253 61.86 Family of Active3 4213 39.14 657443 38.04 Ret/Surv/Fam <654 1 0.01 76 0.00 Ret/Surv/Fam 65+

KMILWAT1 - Wait <4 wks for well patient visit-Mil


. 8049 74.78 1191049 68.91 Missing/Unknown/NA1 2571 23.89 509680 29.49 Yes2 144 1.34 27678 1.60 No

KCIVWAT1 - Wait <4 wks for well patient visit-Civ



KMILOFFC - Office wait of 15 min or more-Mil



05/18/23 155


KCIVOFFC - Office wait of 15 min or more-Civ



KBGPRB1 - Big problem getting referrals to spclst



KBGPRB2 - Big problem getting neccessary care



KMILOP - Outpatient visits to Military facility


A 15 0.14 3301 0.19 Mult response. 27 0.25 5172 0.30 No response1 6726 62.49 926223 53.59 None2 621 5.77 124748 7.22 13 898 8.34 177593 10.27 24 874 8.12 174960 10.12 35 665 6.18 132187 7.65 46 715 6.64 140906 8.15 5-97 223 2.07 43318 2.51 10 or More

05/18/23 156


KCIVOP - Outpatient visits to Civilian facility


A 20 0.19 2467 0.14 Mult response. 25 0.23 3183 0.18 No response1 5713 53.08 1066010 61.68 None2 752 6.99 101898 5.90 13 1137 10.56 155717 9.01 24 1022 9.49 134541 7.78 35 761 7.07 97998 5.67 46 1013 9.41 125154 7.24 5-97 321 2.98 41439 2.40 10 or More

KCIVINS - Beneficiary covered by civilian insuranc


1 442 4.11 53031 3.07 Yes2 10322 95.89 1675376 96.93 No

BWT - BWT - Basic Sampling Weight



19.224 -- 24.269 1511 14.04 96066 5.56 >10th to 25th Percentile27.292 -- 61.611 2504 23.26 427267 24.72 >25th to 50th Percentile66.212 -- 66.252 5213 48.43 1129060 65.32 >50th to 100th Percentile

05/18/23 157


POP - DEERS population by CELLNAME for weights


16761 353 3.28 16761 0.97 1676120140 360 3.34 20088 1.16 2014020195 329 3.06 20195 1.17 2019520403 401 3.73 20265 1.17 2040321264 372 3.46 21264 1.23 2126424838 394 3.66 24598 1.42 2483824916 317 2.95 24841 1.44 2491627167 420 3.90 27167 1.57 2716730557 405 3.76 30557 1.77 3055735210 211 1.96 35210 2.04 3521040919 249 2.31 40768 2.36 4091955640 321 2.98 55308 3.20 5564061347 292 2.71 61347 3.55 6134761573 295 2.74 61152 3.54 6157367508 338 3.14 67508 3.91 6750869483 340 3.16 69483 4.02 6948379917 463 4.30 79917 4.62 7991781661 355 3.30 81419 4.71 8166187470 419 3.89 87266 5.05 8747094785 475 4.41 93937 5.43 9478597436 398 3.70 97436 5.64 97436101809 522 4.85 101809 5.89 101809106995 489 4.54 106768 6.18 106995115524 552 5.13 115524 6.68 115524118315 511 4.75 118315 6.85 118315120792 538 5.00 120792 6.99 120792128915 645 5.99 128713 7.45 128915

WRWT - Final Weight




05/18/23 158


WRWT1 - Replicated/JackKnife Weight 1












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APPENDIX B

CROSSWALK FOR 1999 AND 2000 CHILD QUESTIONNAIRES

05/18/23 179

05/18/23 180

2000 ChildQuestion Number Identical to

2000Difference Between 1999 and 2000 Questions

2000 1999- Version 1

1999- Version 2

C00001 Q1 C00002 Q2 Q1 Q1 Additional response categories in 2000C00003 Q3 Q3 Q3 In 1999, only asked about continuous enrollment in TRICARE PrimeC00004 Q4 Q58 Q58 Additional response categories in 2000C00005 Q5 Q4 Q4

C00006 Q6 Q5 Q5

C00007 Q7 Q6 Q6

C00008 Q8 Q7 Q7

C00009 Q9 Q8 Q8

C00010 Q10 Q9 Q9

C00011 Q11 Q10 Q10

C00012 Q12 Q11 Q11 Question and response categories worded differentlyC00013 Q13 Q12 Q12

C00014 Q14 Q13 Q13

C00015 Q15 Q14 Q14

C00016 Q16 Q15 Q15

C00017 Q17 Q16 Q16

C00018 Q18 Q17 Q17

C00019 Q19 Q18 Q18 Question in 1999 included phrase ‘or advice’C00020 Q20 Q19 Q19

C00021 Q21 Q20 Q20

C00022 Q22 Q21 Q21

C00023 Q23 Q22 Q22

C00024 Q24 Q23 Q23

C00025 Q25 Q24 Q24

B-181

C00026 Q26 Q25 Q25

C00027 Q27 Q26 Q26

C00028 Q28 Q27 Q27 Different response categoriesC00029 Q29 Q28 Q28 Different response categoriesC00030 Q30 Q29 Q29

C00031 Q31 Q30 Q30

C00032 Q32 Q31 Q31

C00033 Q33 Q32 Q32 Question changed from ‘more than 30 minutes’ to ‘more than 15 minutes’C00034 Q34 Q33 Q33

C00035 Q35 Q34 Q34

C00036 Q36 Q35 Q35

C00037 Q37 Q36 Q36

C00038 Q38 Q37 Q37

C00039 Q39 Q38 Q38

C00040 Q40 Q39 Q39

C00041 Q41 Q40 Q40

C00042 Q42 Q41 Q41

C00043 Q43 Q42 Q42 Different response categoriesC00044 Q44 Q44 Q44

C00045 Q45 Q45 Q45

C00046 Q46 Q46 Q46

C00047 Q47 Q47 Q47

C00048 Q48 Q48 Q48

C00049 Q49 Q49 Q49

C00050 Q50 Q50 Q50

C00051 Q51 Q51 Q51

C00052 Q52 Q52 Q52

C00053 Q53 Q53 Q53

C00054 Q54 Q54 Q54

C00055 Q55 Q55 Q55

C00056 Q56 Q56 Q56

C00057 Q57 Q57 Q57

C00058 Q58 Q61 Q61

B-182

C00059 Q59 Q62 Q62

C00060 Q60 C00061 Q61 Q62A Q62A, Q62B Version 2 of the 1999 questionnaire split this question into 2 different parts; Version

1 and 2000 are identical. C00062 Q62 Q63 Q63

C00063 Q63 C00064 Q64 Q63A Q63Q,

Q63BVersion 2 of the 1999 questionnaire split this question into 2 different parts; Version 1 and 2000 are identical.

C00065 Q65 Q64 Q64


1 and 2000 are identical.C00068 Q68 Q65 Q65


1 and 2000 are identical. C00071 Q71 Q66 Q66

C00072 Q72 Q66A Q66A, Q66B Version 2 of the 1999 questionnaire split this question into 2 different parts; Version 1 and 2000 are identical.

C00073 Q73 C00074 Q74 Q68 Q69 Different response categoriesC00075 Q75 C00076 Q76 C00077 Q77 C00078 Q78 Q69 Q70

C00079 Q79 Q70 Q71

C00080 Q80 Q71 Q72

C00081 Q81 Q72 Q73

C00082 Q82 Q73 Q74

C00083 Q83 Q74 Q75

C00084 Q84 Q75 Q76

B-183

APPENDIX C

CODING SCHEME AND CODING TABLES

2000 HEALTH CARE SURVEY OF DOD BENEFICIARIES CHILD QUESTIONNAIRE

CODING SCHEME AND CODING TABLES

BASIC SAS AND ASCII/EBCDIC MISSING DATA AND NOT APPLICABLE CODES

SAS ASCII/EBCDICNumeric Numeric Description

. -9 NO RESPONSE

.A -8 Multiple response error

.O -7 Out of range error

.N -6 Not Applicable or valid skip

.D -5 Scalable response of “Don’t know” or “not sure”.I -4 Incomplete grid error.C -1 Question should not have been answered. It

should have been skipped

Missing values ‘.’, multiple responses ‘.A’, and incomplete grids ‘.I’ are encoded prior to implementation of the Coding Scheme Notes (see below).

Coding Table for Note 2:C00005, C00006 – C00008

N2 C00005 is: C00006 – C00008are:

C00005 is coded as:

C00006 – C00008are coded as:

*

1 1: yes At least one is “marked” or “all are

Stands as original Value

Stand as original Value

C-186

blank”

2 1: yes, missing, or multiple response

“Blank or NA” 2: No .N, valid skip if missing;.C, question should be skipped if marked

B

3 2: no, missing, or multiple response

At least one is “marked”

1: yes Stand as original value B

4 2: no “Blank or NA” or “all are blank”

Stands as original value

.N, valid skip if missing; .C, question should be skipped if –6

F

5 Missing response “All are blank” Stands as original value

Stand as original value

6 Multiple response “All are blank” 2: no .N, valid skip B* Indication of backward coding (B) or forward coding (F).

Definition of “all are blank” in Coding Table for Note 2:All responses to questions C00005 through C00008 are missing.

Definition of “blank or NA” in Coding Table for Note 2:Responses to C00006 through C00008 are either all not applicable (-6) or a combination of missing and not applicable (-6).

Definition of “marked” in Coding Table for Note 2:Any pattern of marks outside the definitions “all are blank,” and “blank or NA.”

C-187

Coding Table for Note 3:C00006 – C00008

N3 C00006 is:

C00007 & C00008 Are:

C00006 is coded as:

C00007 & C00008 are coded as:

*

1 .N, valid skip;.C, question should be skipped

Any mark or missing response


.N, valid skip if missing;

.C, question should be skipped if marked

F

2 >= 1, missing, or multiple response

At least one is “marked” Stands as original value


3 >=1 or multiple response

“Blank or NA” or “all are blank”

-6: no personal doctor or nurse



BF

4 Missing response “Blank or NA” -6: no personal doctor .N, Valid skip if missing;.C, question should be skipped if marked

BF



* Indication of backward coding (B) or forward coding (F).

Definition of “all are blank” in Coding Table for Note 3:Responses to question C00006 and C00007 are both missing.

Definition of “blank or NA” in Coding Table for Note 3:Responses to C00006 and C00007 are either both not applicable (-6), or a combination of missing and not applicable (-6).

Definition of “marked” in Coding Table for Note 3:Any pattern of marks outside the definitions “all are blank,” and “blank or NA.”

Coding Table for Note 4:C00007, C00008

N4 C00007 is:

C00008 is:

C00007is coded as:

C00008 is coded as:

*


Any mark or missing response




F


>=1, missing, or multiple response



3 >=1, missing, or multiple response




BF


C-188


N5 C00009 is:

C00010 – C00012 are :

C00009 is coded as:

C00010 – C00012 Are:

*

1 1: yes “All are blank” Stands as original value Stand as original value2 1: yes, missing, or

multiple responseAt least one is “marked” 1: yes Stand as original value B


“Blank or NA” 2: no .N, valid skip if missing;.C, question should be skipped if marked

BF

4 2: no,-5: I don’t know, or-6: not enrolled in Tricare Prime

“All are blank” Stands as original value .N, valid skip F

5 2: no,-5: I don’t know, or –6: not enrolled in Tricare Prime

At least one is “marked” 1: yes Stand as original value B

6 2:no,-5: I don’t know, -6: not enrolled in Tricare Prime


BF

7 Multiple response “All are blank” -5: I don’t know .N, valid skip if missing;.C, question should be skipped if marked

BF

8 Missing response “All are blank” Stands as original value Stand as original value* Indication of backward coding (B) or forward coding (F).

DEFINITION OF “ALL ARE BLANK” IN CODING TABLE FOR NOTE 5:ALL RESPONSES TO QUESTIONS C00010 THROUGH C00012 ARE MISSING.

DEFINITION OF “BLANK OR NA” IN CODING TABLE FOR NOTE 5:RESPONSES TO QUESTIONS C00010 AND C00012 ARE MISSING, THE RESPONSE TO QUESTION C00011 IS –6, “MY CHILD DOESN’T HAVE A TRICARE PRIMARY CARE MANAGER.”

DEFINITION OF “MARKED” IN CODING TABLE FOR NOTE 5:ANY PATTERN OF MARKS OUTSIDE OF “ALL ARE BLANK” AND “BLANK OR NA.”


N6 C00011 is:

C00012 is:

C00011is coded as:

C00012 is coded as:

*


.N, valid skip;

.C, question should be skipped




Marked, missing, or multiple response



3 -6: no personal doctor or nurse

Marked, missing, or multiple response




F


Coding Table for Note 7:

C-189

C00013 – C00017N7 C00013 is: C00014 -C00017

are: C00013 is coded as:

C00014-C00017are coded as:

*

1 1: yes “At least one is “marked” or “all are blank,”




“Blank or no usage or NA”

2: no .N, valid skip if missing;.C, question should be skipped if marked

BF



1: yes Stand as original value

F

4 2: no “Blank or no usage or NA” or “all are blank”


.N, valid skip if missing;.C, question should be skipped if marked

F



6 Multiple response “All are blank” 2: no .N, valid skip BF


DEFINITION OF “ALL ARE BLANK” IN CODING TABLE FOR NOTE 7:ALL RESPONSES TO QUESTIONS C00014 THROUGH C00017 ARE MISSING.

DEFINITION OF “BLANK OR NO USAGE OR NA” IN CODING TABLE FOR NOTE 7:ALL OF THE FOLLOWING ARE TRUE: C00015 IS EITHER ‘2’ OR MISSING, C00014, C00016, C00017 ARE EITHER NOT APPLICABLE OR MISSING.

DEFINITION OF “MARKED” IN CODING TABLE FOR NOTE 7:ANY PATTERN OF MARKS OUTSIDE OF “ALL ARE BLANK,” AND “BLANK OR NA.”


N8 C00015 is: C00016 & C00017 C00015 is coded as: C00016 & C00017 *

C-190

are: are coded as:1 .N, valid skip;


.N, valid skip;




2 1: yes At least one is “marked” or “all are blank”





BF







F




DEFINITION OF “ALL ARE BLANK” IN CODING TABLE FOR NOTE8:BOTH C00016 AND C00017 ARE MISSING.

DEFINITION OF “BLANK OR NA” IN CODING TABLE FOR NOTE 8:RESPONSES TO QUESTIONS C00016 AND C00017 ARE A COMBINATION OF –6 (NOT APPLICABLE) AND MISSING OR BOTH –6(NOT APPLICABLE).

DEFINITION OF “MARKED” IN CODING TABLE FOR NOTE 8:ANY PATTERN OF MARKS OUTSIDE OF “BLANK OR NA.”


N9 C00018 is: C00019 is : C00018 is coded as: C00019 is coded as: *1 1: yes 1-4: how often,

missing, or multiple response




-6: no calls 2: no .C, question should be skipped

BF

3 2: no, missing or multiple response

1-4: how often or multiple response

1: yes Stands as original value B

4 2: no -6: no calls, or missing response


.N, valid skip F

5 Missing response Missing response Stands as original value


6 Multiple response Missing response 2: no .N, valid skip B* Indication of backward coding (B) or forward coding (F).


N10 C00020 C00021 & C00022 C00020 C00021 & C00022 *

C-191

is: are: is coded as: are coded as:1 1: yes “All are blank” or at

least one is “marked”





BF








F





Definition of “blank or NA” in Coding Table for Note 10:Responses to questions C00021 and C00022 are either both not applicable (–6), or a combination of not applicable (-6) and missing.

Definition of “marked” in Coding Table for Note 10:Any pattern of marks outside “all are blank” or “blank or NA.”


N11 C00023 is:

C00024 & C00025are:

C00023 is coded as:

C00024 & C00025are coded as:

*

1 1: yes “All are blank” or at least one is “marked”





BF








F






C-192



N12 C00026 is:

C00027 & C00028 are:

C00026 is coded as:


*






BF








F







C-193

Coding Table for Note 13C00030, C00031 -- C00042

N13 C00030 is:

C00030 – C00042 are:

C00030is coded as:

C00031 -- C00042 are coded as:

*

1 1: none “Blank or No Usage or NA” or “all are blank”

Stands as original value .N, valid skip if missing; .C, question should be skipped if marked

F

2 1, missing or multiple response

At least one is “marked” Stands as original value Stands as original value

3 >=2 At least one is “marked” or “all are blank”

Stands as original value Stand as original value

4 >=2, missing, or multiple response

“Blank or No Usage or NA”

1: none .N, valid skip if missing;.C, question should be skipped if marked

BF

5 Missing response

“All are blank” Stands as original value Stand as original value

6 Multiple response

“All are blank” 1: none .N, valid skip B



Definition of “blank or no usage or NA” in Coding Table for Note 13:All of the following are true: C00031 – C00038, C00040 – C00042 are either not applicable (-6), or a combination of not applicable (-6) and missing, and C00039 is any value or missing.

Definition of “marked” in Coding Table for Note 13:Any pattern of marks outside the definitions “all are blank” and “blank or no usage or NA.”

C-195

Coding Table for Note 14C00039, C00040

N14 C00039 IS:

C00040 is:

C00039 is coded as:

C00040 is coded as:

*

1 .N, valid skip or.C, question should not have been answered

.N, valid skip or .C, question should not have been answered



2 1: yes Missing Stands as original value


3 1: yes -6: not applicable .C, question should be skipped


BF


Any mark but –6: not applicable

1: yes Stands as original value

B

5 Missing or multiple response

-6: not applicable 2: no .C, question should be skipped

BF

6 2: no Any mark but –6: not applicable


B

7 2: no Missing or –6: not applicable



F

8 Missing Missing Stands as original value


9 Multiple response Missing 2: no .N, valid skip B* Indication of backward coding (B) or forward coding (F).

C-196

Coding Table for Note 15:C00044, C00045 -- C00047

N15 C00044 Is:

C00045 -- C00047 are:

C00044 is coded as:

C00045 – C00047are coded as:

*

1 1: yes At least one is “marked” or “all are blank”

Stands as original value Stand as original value

2 1: yes,-6: don’t know, missing, or multiple response

“All are NA” 2: no .C, question should be skipped

B



B

4 2: no,-6: don’t know, missing, or multiple response


5 2: no or-6: don’t know

“Blank or NA” or “all are blank”

Stands as original value .N, valid skip if missing;.C, question should be skipped if marked

F

6 2: no “All are NA” Stands as original value .C, question should be skipped

F

7 Missing response “All are blank” Stands as original value Stands as original value8 Multiple response “All are blank” 2: no .N, valid skip B



Definition of “all are NA” in Coding Table for Note 15:All responses to questions C00045 through C00047 are “No claims were sent to the health plan in the past 12 months”, i.e. not applicable (-6). Definition of “blank or NA” in Coding Table for Note 15:Responses to C00045 through C00047 are either all not applicable (-6) or a combination of missing and not applicable (-6).

Definition of “marked” in Coding Table for Note 15:Any pattern of marks outside the definitions “all are blank”, “all are NA”, and “blank or NA”

C-197


N16 C00048 is: C00049 is: C00048 is coded as: C00049 is coded as: *1 1: yes 1-3: categorize

problem, missing, or multiple response





BF


1-3: categorize problem, or multiple response


4 2: no -6: not applicable or missing response




F



6 Multiple response Missing response 2: no .N, valid skip B* Indication of backward coding (B) or forward coding (F)


N17 C00050 is: C00051 is : C00050 is coded as: C00051 is coded as: *1 1: yes 1-3: categorize






BF








F




C-198


N18 C00052 is:

C00053 & C00054 are:

C00052 is coded as:


*






BF








F








N19 C00053 is: C00054 is: C00053 is: C00054 is: *1 .N, valid skip;


.N, valid skip;




2 1 – 5: time to resolve claim, missing, or multiple response

1:yes, 2:no, missing or multiple response



3 6: still waiting 1:yes, 2:no, missing or multiple response



F

4 1 – 6: time to resolve claim, still waiting, missing, or multiple response

3: still waiting 6: still waiting Stands as original value

B

5 1-6: time to resolve -6: haven’t called Stands as original Stands as original

C-199

claim, still waiting or multiple response

value value

6 -6: haven’t called 1: yes, 2: no,multiple response



7 -6: haven’t called 3: still waiting 6: still waiting Stands as original value

B

* Indication of backward coding (B) or forward coding (F).Coding Table for Note 20:C00055, C00056

N20 C00055 is: C00056 is : C00055 is coded as: C00056 is coded as: *1 1: yes 1-3: categorize






BF




B



.N, valid skip if missing, .C, question should be skipped if marked

F




Coding Table for Note 21:C00059, C00060 & C00061

N21 C00059 is: C00060 & C00061Are:

C00059 is coded as:


*

1 1: yes “All are blank” Stands as original value


2 1: yes, missing or multiple response

At least one is “marked” or “blank or no”

1:yes Stand as original value B

3 2: no At least one is “marked”

1: yes Stand as original value F

4 2: no “All are blank” or “blank or no”


.N, valid skip if missing,


F



6 Multiple response “All are blank” 2:no .N, valid skip if missing.C, question should be skipped if marked

BF


Definition of “all are blank” in Coding Table for Note 21:

C-200

Responses to question C00060 and C00061 are both missing.

Definition of “blank or no” in Coding Table for Note 21:Responses to questions C00060 and C00061 are either both no (2), or a combination of no (2) and missing.



N22 C00060 is:

C00061 is :

C00060 is coded as:

C00061 is coded as:

*

1 .N, valid skip or.C, question should be skipped

.N, valid skip or


Stands as original value Stands as original value

2 1: yes Marked, missing, or multiple response


3 2:no 2: no, missing Stands as original value .N, valid skip if missing;.C, question should be skipped if marked

F

4 2:no, missing, or multiple response

1: yes or multiple response



2: no 1: yes Stands as original value B

6 Missing response Missing Stands as original value Stands as original value7 Multiple response Missing 2: no .N, valid skip B *Indication of backward coding (B) or forward coding (F).


N23 C00062 is: C00063 & C00064are:

C00062 is coded as:


*

1 1: yes “All are blank” or “blank or no”












F



6 Multiple response “All are blank” 2:no .N, valid skip BF



C-201




N24 C00063 is:

C00064 is :

C00063 is coded as:

C00064 is coded as:

*


.N, valid skip or






F








N25 C00065 is: C00066 & C00067are :

C00065 is coded as:


*













F



6 Multiple response “All are blank” 2:no .N, valid skip if missing BF


Definition of “all are blank” in Coding Table for Note 25:

C-202

Responses to question C00066 and C00067 are both missing.




N26 C00066 is:

C00067 is :

C00066 is coded as:

C00067 is coded as:

*


.N, valid skip or






F








N27 C00068 is: C00069 & C00070are :

C00068 is coded as:


*













F



6 Multiple response “All are blank” 2:no .N, valid skip if missing BF


C-203



Definition of “marked” in Coding Table for Note 27:Any pattern of marks outside “all are blank” or “blank or NA.”Coding Table for Note 28:C00069, C00070

N28 C00069 is:

C00070 is:

C00069 is coded as:

C00070 is coded as:

*


.N, valid skip or






F








N29 C00071 is:

C00072 is :

C00071 is coded as:

C00072is coded as:

*

1 1: yes Marked , missing, or multiple response

Stands as original value Stands as original value F

2 2:no Missing response Stands as original value .N, valid skip3 2:no, missing or

multiple response1: yes, 2: no, or multiple response


4 Missing Missing Stands as original value Stands as original value5 Multiple response Missing 2: no .N, valid skip B *Indication of backward coding (B) or forward coding (F).

C-204

Coding Table for Note 30:C00074, C00075-77

N30

C00074 is:

C00075is

C00076A-C00076Fare :

C00077is

C00074 is coded as:

C00075 is coded as:

C00076A-C00076Fare coded as:

C00077is coded as:

*

1 1: < 1year

Marked or missing

Marked or missing

Marked or missing



N, valid skip if missing;.C, question should be skipped if marked


F

2 2: 1-2 years

Marked or missing

Marked or missing

Marked or missing





3 3-6 Marked or missing

Marked or missing

Marked or missing


.N, valid skip if missing; .C, question should be skipped if marked



F

4 Missing or Multiple response

Marked Marked or missing

Marked or Missing

2: 1-2 years Stands as original value



B


Missing Any marked

Marked or missing

2: 1-2 years Stands as original value



F


Missing Missing Marked or missing





*Indication of backward coding (B) or forward coding (F).

C-206

APPENDIX D

SAS PROC CONTENTS—ALPHABETICAL CHILD 2000

C-207

The SAS System 15:05 Wednesday, December 12, 2001 1

CONTENTS PROCEDURE

Data Set Name: IN.HCS00C_1 Observations: 10764 Member Type: DATA Variables: 255 Engine: V612 Indexes: 0 Created: 10:45 Wednesday, December 12, 2001 Observation Length: 1368 Last Modified: 10:45 Wednesday, December 12, 2001 Deleted Observations: 0 Protection: Compressed: YES Data Set Type: Reuse Space: NO Sorted: NO Label:

-----Engine/Host Dependent Information-----

Data Set Page Size: 16384 Number of Data Set Pages: 830 File Format: 607

-----Alphabetic List of Variables and Attributes----- # Variable Type Len Pos Format Informat Label --------------------------------------------------------------------------------------------- 5 AGESMPL Num 8 23 AGESMPL. AGESMPL - Age 6 BGCSMPL Num 8 31 XBGC_S. BGCSMPL - Beneficiary Group 193 BWT Num 8 864 BWT - Basic Sampling Weight 32 C00001 Num 4 134 CYN2_. 11. Are you adult responsible for child 33 C00002 Num 4 138 CPLAN1_. 11. Which hlth plan did you use most 34 C00003 Num 4 142 CENROLL. 11. In last 12 mos,# mos in a row cvrd w/Pln 44 C00005 Num 4 182 CYN2_. 11. Does child have personal Dr/Nurse 45 C00006 Num 4 186 CPROB1_. 11. How much prblem to get personal Dr/Nurse 46 C00007 Num 4 190 COFTN1_. 11. Talk about feeling/growing/behaving 47 C00008 Num 4 194 CRATE1_. 11. Rating of childs personal Dr/Nurse 48 C00009 Num 4 198 CYN3_. 11. Does child have primary care manager 49 C00010 Num 4 202 CYN2_. 11. Know name of childs Primary care mgr 50 C00011 Num 4 206 CPROB2_. 11. In last 12 mos how much prblm to see PCM 51 C00012 Num 4 210 CWORK. 11. Is primary care mgr military or civilian 52 C00013 Num 4 214 CYN2_. 11. Did you think child needed to see spclst 53 C00014 Num 4 218 CPROB3_. 11. How much prblm to get referral to spclst 54 C00015 Num 4 222 CYN2_. 11. In last 12 mos did child see specialist 55 C00016 Num 4 226 CRATE2_. 11. Rating of specialist seen most often 56 C00017 Num 4 230 CYN4_. 11. Specialist same as personal Dr 57 C00018 Num 4 234 CYN2_. 11. Call during reg. Hrs to get help/advice 58 C00019 Num 4 238 COFTN2_. 11. Called during reg Hrs did you get hlp 59 C00020 Num 4 242 CYN2_. 11. Make appt for regular/routine hlthcre 60 C00021 Num 4 246 COFTN3_. 11. How oftn get appt for care soon as wnted 61 C00022 Num 4 250 CDAYS1_. 11. Wait btwn mking appt and seeing provider 62 C00023 Num 4 254 CYN2_. 11. Have illness/injury need care right away 63 C00024 Num 4 258 COFTN4_. 11. Get needed care as soon as wanted 64 C00025 Num 4 262 CDAYS2_. 11. Wait btwn trying to & seeing provider 65 C00026 Num 4 266 CYN2_. 11. Appointment for well-patient care 66 C00027 Num 4 270 COFTN5_. 11. Get appt for well-patient care November 27, 2001

D-209


CONTENTS PROCEDURE

# Variable Type Len Pos Format Informat Label --------------------------------------------------------------------------------------------- 67 C00028 Num 4 274 CLONG. 11. Wait to see provider for well-patnt care 68 C00029 Num 4 278 CTIMESA. 11. Times to ER 69 C00030 Num 4 282 CDOCCLIN. 11. Times to Dr office/Clinic (excluding ER) 70 C00031 Num 4 286 CPROB4_. 11. Problem to get necessary care 71 C00032 Num 4 290 CPROB4_. 11. Problem wait for approval 72 C00033 Num 4 294 COFTN6_. 11. How oftn wait >15 mins 73 C00034 Num 4 298 COFTN6_. 11. How oftn staff treat w/courtesy &respect 74 C00035 Num 4 302 COFTN6_. 11. How oftn were staff helpful 75 C00036 Num 4 306 COFTN6_. 11. How oftn did staff listen carefully 76 C00037 Num 4 310 COFTN6_. 11. How oftn did staff explain things to you 77 C00038 Num 4 314 COFTN6_. 11. How oftn staff respect what had to say 78 C00039 Num 4 318 CYN2_. 11. Child old enough to talk to Dr 79 C00040 Num 4 322 COFTN7_. 11. Dr explain in way for child to undrstnd 80 C00041 Num 4 326 COFTN6_. 11. How oftn spend enough time w/child 81 C00042 Num 4 330 CRATE3_. 11. Rating of childs healthcare 82 C00043 Num 4 334 CTYPE. 11. Type of facility child used most often 83 C00044 Num 4 338 CYN1_. 11. Send in any claims 84 C00045 Num 4 342 COFTN8_. 11. Handle claim in reasonable time 85 C00046 Num 4 346 COFTN8_. 11. Handle claim correctly 86 C00047 Num 4 350 COFTN8_. 11. Plan make clear how much to pay 87 C00048 Num 4 354 CYN2_. 11. Look for info/written material 88 C00049 Num 4 358 CPROB5_. 11. Find/understand info in written material 89 C00050 Num 4 362 CYN2_. 11. Call customer service to get info 90 C00051 Num 4 366 CPROB6_. 11. Problem get help when call customer svc 91 C00052 Num 4 370 CYN2_. 11. Called/written plan with complaint 92 C00053 Num 4 374 CSOLVE. 11. How long to resolve complaint 93 C00054 Num 4 378 CYN5_. 11. Complaint/problem settled to satisfction 94 C00055 Num 4 382 CYN2_. 11. Experience with paperwork 95 C00056 Num 4 386 CPROB7_. 11. Problem with paperwork 96 C00057 Num 4 390 CRATE4_. 11. Rating of exprience with child hlth plan 97 C00058 Num 4 394 CHEALTH. 11. Rate child overall health 98 C00059 Num 4 398 CYN2_. 11. Child use medicine prescribed by Dr 99 C00060 Num 4 402 CYN2_. 11. Medicine b/c medical,behavioral,other 100 C00061 Num 4 406 CYN2_. 11. Medicine b/c cndtn expected last>=12 mos 101 C00062 Num 4 410 CYN2_. 11. Mre medical,mntl,edcution svcs thn usual 102 C00063 Num 4 414 CYN2_. 11. Use svcs b/c medical, behavioral, oth 103 C00064 Num 4 418 CYN2_. 11. Svcs b/c condition expected last>=12 mos 104 C00065 Num 4 422 CYN2_. 11. Limited/prevented in ability 105 C00066 Num 4 426 CYN2_. 11. Limited b/c medical, behavioral, other 106 C00067 Num 4 430 CYN2_. 11. Limited b/c condition expected last>=1yr 107 C00068 Num 4 434 CYN2_. 11. Get special therapy 108 C00069 Num 4 438 CYN2_. 11. Therapy b/c medical, behavioral, other 109 C00070 Num 4 442 CYN2_. 11. Therapy b/c condition expected last>=1yr 110 C00071 Num 4 446 CYN2_. 11. Problem for which gets trtmnt/counseling 111 C00072 Num 4 450 CYN2_. 11. Trtmnt/counseling b/c conditn last>=1yr 112 C00073 Num 4 454 CPREVENT. 11. Last time routine preventive care appt 113 C00074 Num 4 458 CAGE1_. 11. Childs age now November 27, 2001

D-210


CONTENTS PROCEDURE

# Variable Type Len Pos Format Informat Label --------------------------------------------------------------------------------------------- 114 C00075 Num 4 462 CYN1_. 11. Child recd all immunizations 129 C00078 Num 4 522 CSEX. 11. Is child male or female 130 C00079 Num 4 526 CHISP. 11. Is child Hispanic/Latino 136 C00081 Num 4 550 CAGE2_. 11. Your age now 137 C00082 Num 4 554 CSEX. 11. Are you male or female 138 C00083 Num 4 558 CRELEDU. 11. highest grade/level you completed 139 C00084 Num 4 562 CRELATE. 11. How related to child 35 C00004A Num 4 146 CMARK. 11. Child covered by TRICARE Prime 36 C00004B Num 4 150 CMARK. 11. Child covered by TRICARE Extra/Standard 37 C00004C Num 4 154 CMARK. 11. Child covered by Fed. EMP Health Benefit 38 C00004D Num 4 158 CMARK. 11. Child covered by Medicaid 39 C00004E Num 4 162 CMARK. 11. Child covered by Civilian HMO 40 C00004F Num 4 166 CMARK. 11. Child covered by Other Civilian Ins. 41 C00004G Num 4 170 CMARK. 11. Child covered by USFP 42 C00004H Num 4 174 CMARK. Not sure who Child covered by 43 C00004I Num 4 178 CMARK. Child did not use health plan last 12mos 115 C00076A Num 4 466 CVACCINE. 11. # times child recd Dtap,DT,DTP 116 C00076B Num 4 470 CVACCINE. 11. # times child recd MMR 117 C00076C Num 4 474 CVACCINE. 11. # times child recd IPV or OPV 118 C00076D Num 4 478 CVACCINE. 11. # times child recd Hib 119 C00076E Num 4 482 CVACCINE. 11. # times child recd HepB 120 C00076F Num 4 486 CVACCINE. 11. # times child recd Varicella 121 C00077A Num 4 490 CMARK. 11. Talk about growth/development 122 C00077B Num 4 494 CMARK. 11. Talk about behaviors to expect 123 C00077C Num 4 498 CMARK. 11. Talk about dress/bathe/feed child 124 C00077D Num 4 502 CMARK. 11. Talk about help child grow/learn 125 C00077E Num 4 506 CMARK. 11. Talk about tlking/reading/plying w/child 126 C00077F Num 4 510 CMARK. 11. Talk about keep child from injured 127 C00077G Num 4 518 CMARK. 11. Talk about make house safe 128 C00077H Num 4 514 CMARK. 11. Talk about make car safe 131 C00080A Num 4 530 CMARK. 11. Child race:white 132 C00080B Num 4 534 CMARK. 11. Child race:Black 133 C00080C Num 4 538 CMARK. 11. Child race:Asian 134 C00080D Num 4 542 CMARK. 11. Child race:Native Hawaiian/Pacific Islnd 135 C00080E Num 4 546 CMARK. 11. Child race:Am. Indian/Alaskan 179 CONUS Num 3 757 CONUSMHS. CONUS - CONUS/OCONUS Indicator 13 DAGEQY Char 3 59 Age (As of 31 January 2001) 20 DBENCAT Char 3 82 $BENCAT. Beneficiary Category 26 DCATCH Char 4 99 Catchment Area 21 DMEDELG Char 1 85 $MEDELG. Medical Privlege Code 22 DSPONSVC Char 1 86 $SPONSVC. Derived Sponsor Branch of Service 141 DUPFLAG Char 3 570 Multiple Response Indicator 8 ENBGSMPL Char 2 44 $ENBGS. Enrollment by beneficiary category 28 ENLSMPL Num 8 107 ENLSMP. ENLSMPL - Enrollment Sampling Group 25 ENRID Char 4 95 Enrollment DMISID 14 FIELDAGE Char 3 62 Age as of July 1st 2001 140 FLAG_FIN Char 4 566 $FINAL. $5. Final Disposition November 27, 2001

D-211


CONTENTS PROCEDURE

# Variable Type Len Pos Format Informat Label --------------------------------------------------------------------------------------------- 29 FNSTATUS Num 8 115 FNSTATS. Final Status 188 KBGPRB1 Num 8 824 HAYNN. Big problem getting referrals to spclst 189 KBGPRB2 Num 8 832 HAYNN. Big problem getting neccessary care 192 KCIVINS Num 8 856 HAYNN2_. Beneficiary covered by civilian insuranc 187 KCIVOFFC Num 8 816 HAYNN. Office wait of 15 min or more-Civ 191 KCIVOP Num 8 848 CTIMES. Outpatient visits to Civilian facility 185 KCIVWAT1 Num 8 800 HAYNN. Wait <4 wks for well patient visit-Civ 30 KEYCOUNT Num 8 123 # of Key Questions Answered 186 KMILOFFC Num 8 808 HAYNN. Office wait of 15 min or more-Mil 190 KMILOP Num 8 840 CTIMES. Outpatient visits to Military facility 184 KMILWAT1 Num 8 792 HAYNN. Wait <4 wks for well patient visit-Mil 17 LEGDDSCD Char 2 78 $DDSFMT. DDS Code 19 MBRRELCD Char 1 81 $MBRREL. Member Relationship Code 23 MEDTYPE Char 1 87 $MEDTYP. Medicare Type 171 MISS_1 Num 8 693 HAMISS. Count of: Violates Skip Pattern 172 MISS_4 Num 8 701 HAMISS. Count of: Incomplete grid error 173 MISS_5 Num 8 709 HAMISS. Count of: Dont know or not sure 174 MISS_6 Num 8 717 HAMISS. Count of: Not applicable - valid skip 175 MISS_7 Num 8 725 HAMISS. Count of: Out-of-range error 176 MISS_8 Num 8 733 HAMISS. Count of: Multiple response error 177 MISS_9 Num 8 741 HAMISS. Count of: No response - invalid skip 178 MISS_TOT Num 8 749 HAMISS. Total number of missing responses 2 MPCSMPL Num 5 8 MPCSMPL. MPCSMPL - Military Personnel Category 1 MPRID Char 8 0 $42. $42. Unique MPR Identifier 11 MRTLSTAT Char 1 57 $MSTATUS. Marital Status 142 N2 Num 4 573 Coding Scheme Note 2 143 N3 Num 4 577 Coding Scheme Note 3 144 N4 Num 4 581 Coding Scheme Note 4 145 N5 Num 4 585 Coding Scheme Note 5 146 N6 Num 8 589 Coding Scheme Note 6 147 N7 Num 4 597 Coding Scheme Note 7 148 N8 Num 4 601 Coding scheme Note 8 149 N9 Num 4 605 Coding scheme Note 9 150 N10 Num 4 609 Coding Scheme Note 10 151 N11 Num 4 613 Coding Scheme Note 11 152 N12 Num 4 617 Coding Scheme Note 12 153 N13 Num 4 621 Coding Scheme Note 13 154 N14 Num 4 625 Coding Scheme Note 14 155 N15 Num 4 629 Coding Scheme Note 15 156 N16 Num 4 633 Coding Scheme Note 16 157 N17 Num 4 637 Coding Scheme Note 17 158 N18 Num 4 641 Coding Scheme Note 18 159 N19 Num 4 645 Coding Scheme Note 19 160 N20 Num 4 649 Coding Scheme Note 20 161 N21 Num 4 653 FORM. Coding Scheme Note 21 162 N22 Num 4 657 FORM. Coding Scheme Note 22 163 N23 Num 4 661 FORM. Coding Scheme Note 23 November 27, 2001

D-212


CONTENTS PROCEDURE

# Variable Type Len Pos Format Informat Label --------------------------------------------------------------------------------------------- 164 N24 Num 4 665 FORM. Coding Scheme Note 24 165 N25 Num 4 669 FORM. Coding Scheme Note 25 166 N26 Num 4 673 FORM. Coding Scheme Note 26 167 N27 Num 4 677 FORM. Coding Scheme Note 27 168 N28 Num 4 681 FORM. Coding Scheme Note 28 169 N29 Num 4 685 FORM. Coding Scheme Note 29 170 N30 Num 4 689 FORM. Coding Scheme Note 30 24 PATCAT Char 7 88 $AGGBCAT. Aggregated Beneficiary Category 15 PCM Char 3 65 $PCM. Primary Manager Code (CIV or MIL) 18 PNLCATCD Char 1 80 $PNLCAT. Personnel Category Code (Duty Status) 194 POP Num 8 872 DEERS population by CELLNAME for weights 31 POSTSTR Char 3 131 Post Stratification Cell 12 RACEETHN Char 1 58 $RACECD. Race/Ethnic Code 7 REGSMPL Num 5 39 CREGSMPL. REGSMPL - Region 4 SEXSMPL Num 5 18 HASEX. SEXSMPL - Sex 9 STRATUM Char 3 46 Sampling STRATUM 10 SUPREG Num 8 49 SUPERREG. SUPREG - Super Region 3 SVCSMPL Num 5 13 SVCSMPL. SVCSMPL - Branch of Service 16 TSPSITE Char 10 68 $TSPSITE. TSP Site (regardless of age) 27 ULOCDMIS Char 4 103 Unit DMISID 195 WRWT Num 8 880 Final Weight 196 WRWT1 Num 8 888 Replicated/JackKnife Weight 1 197 WRWT2 Num 8 896 Replicated/JackKnife Weight 2 198 WRWT3 Num 8 904 Replicated/JackKnife Weight 3 199 WRWT4 Num 8 912 Replicated/JackKnife Weight 4 200 WRWT5 Num 8 920 Replicated/JackKnife Weight 5 201 WRWT6 Num 8 928 Replicated/JackKnife Weight 6 202 WRWT7 Num 8 936 Replicated/JackKnife Weight 7 203 WRWT8 Num 8 944 Replicated/JackKnife Weight 8 204 WRWT9 Num 8 952 Replicated/JackKnife Weight 9 205 WRWT10 Num 8 960 Replicated/JackKnife Weight 10 206 WRWT11 Num 8 968 Replicated/JackKnife Weight 11 207 WRWT12 Num 8 976 Replicated/JackKnife Weight 12 208 WRWT13 Num 8 984 Replicated/JackKnife Weight 13 209 WRWT14 Num 8 992 Replicated/JackKnife Weight 14 210 WRWT15 Num 8 1000 Replicated/JackKnife Weight 15 211 WRWT16 Num 8 1008 Replicated/JackKnife Weight 16 212 WRWT17 Num 8 1016 Replicated/JackKnife Weight 17 213 WRWT18 Num 8 1024 Replicated/JackKnife Weight 18 214 WRWT19 Num 8 1032 Replicated/JackKnife Weight 19 215 WRWT20 Num 8 1040 Replicated/JackKnife Weight 20 216 WRWT21 Num 8 1048 Replicated/JackKnife Weight 21 217 WRWT22 Num 8 1056 Replicated/JackKnife Weight 22 218 WRWT23 Num 8 1064 Replicated/JackKnife Weight 23 219 WRWT24 Num 8 1072 Replicated/JackKnife Weight 24 220 WRWT25 Num 8 1080 Replicated/JackKnife Weight 25 221 WRWT26 Num 8 1088 Replicated/JackKnife Weight 26 November 27, 2001

D-213


CONTENTS PROCEDURE

# Variable Type Len Pos Format Informat Label --------------------------------------------------------------------------------------------- 222 WRWT27 Num 8 1096 Replicated/JackKnife Weight 27 223 WRWT28 Num 8 1104 Replicated/JackKnife Weight 28 224 WRWT29 Num 8 1112 Replicated/JackKnife Weight 29 225 WRWT30 Num 8 1120 Replicated/JackKnife Weight 30 226 WRWT31 Num 8 1128 Replicated/JackKnife Weight 31 227 WRWT32 Num 8 1136 Replicated/JackKnife Weight 32 228 WRWT33 Num 8 1144 Replicated/JackKnife Weight 33 229 WRWT34 Num 8 1152 Replicated/JackKnife Weight 34 230 WRWT35 Num 8 1160 Replicated/JackKnife Weight 35 231 WRWT36 Num 8 1168 Replicated/JackKnife Weight 36 232 WRWT37 Num 8 1176 Replicated/JackKnife Weight 37 233 WRWT38 Num 8 1184 Replicated/JackKnife Weight 38 234 WRWT39 Num 8 1192 Replicated/JackKnife Weight 39 235 WRWT40 Num 8 1200 Replicated/JackKnife Weight 40 236 WRWT41 Num 8 1208 Replicated/JackKnife Weight 41 237 WRWT42 Num 8 1216 Replicated/JackKnife Weight 42 238 WRWT43 Num 8 1224 Replicated/JackKnife Weight 43 239 WRWT44 Num 8 1232 Replicated/JackKnife Weight 44 240 WRWT45 Num 8 1240 Replicated/JackKnife Weight 45 241 WRWT46 Num 8 1248 Replicated/JackKnife Weight 46 242 WRWT47 Num 8 1256 Replicated/JackKnife Weight 47 243 WRWT48 Num 8 1264 Replicated/JackKnife Weight 48 244 WRWT49 Num 8 1272 Replicated/JackKnife Weight 49 245 WRWT50 Num 8 1280 Replicated/JackKnife Weight 50 246 WRWT51 Num 8 1288 Replicated/JackKnife Weight 51 247 WRWT52 Num 8 1296 Replicated/JackKnife Weight 52 248 WRWT53 Num 8 1304 Replicated/JackKnife Weight 53 249 WRWT54 Num 8 1312 Replicated/JackKnife Weight 54 250 WRWT55 Num 8 1320 Replicated/JackKnife Weight 55 251 WRWT56 Num 8 1328 Replicated/JackKnife Weight 56 252 WRWT57 Num 8 1336 Replicated/JackKnife Weight 57 253 WRWT58 Num 8 1344 Replicated/JackKnife Weight 58 254 WRWT59 Num 8 1352 Replicated/JackKnife Weight 59 255 WRWT60 Num 8 1360 Replicated/JackKnife Weight 60 183 XBNFGRP Num 8 784 XBGC_S. Constructed Beneficiary Group 180 XENRLLMT Num 8 760 ENROLL. Enrollment in TRICARE Prime 181 XENR_PCM Num 8 768 PCM. Enrollment by PCM type 182 XINS_COV Num 8 776 INSURE. Insurance Coverage November 27, 2001

D-214

APPENDIX E

SAS PROC CONTENTS—POSITIONAL CHILD 2000

D-215


CONTENTS PROCEDURE -----Variables Ordered by Position----- # Variable Type Len Pos Format Informat Label --------------------------------------------------------------------------------------------- 1 MPRID Char 8 0 $42. $42. Unique MPR Identifier 2 MPCSMPL Num 5 8 MPCSMPL. MPCSMPL - Military Personnel Category 3 SVCSMPL Num 5 13 SVCSMPL. SVCSMPL - Branch of Service 4 SEXSMPL Num 5 18 HASEX. SEXSMPL - Sex 5 AGESMPL Num 8 23 AGESMPL. AGESMPL - Age 6 BGCSMPL Num 8 31 XBGC_S. BGCSMPL - Beneficiary Group 7 REGSMPL Num 5 39 CREGSMPL. REGSMPL - Region 8 ENBGSMPL Char 2 44 $ENBGS. Enrollment by beneficiary category 9 STRATUM Char 3 46 Sampling STRATUM 10 SUPREG Num 8 49 SUPERREG. SUPREG - Super Region 11 MRTLSTAT Char 1 57 $MSTATUS. Marital Status 12 RACEETHN Char 1 58 $RACECD. Race/Ethnic Code 13 DAGEQY Char 3 59 Age (As of 31 January 2001) 14 FIELDAGE Char 3 62 Age as of July 1st 2001 15 PCM Char 3 65 $PCM. Primary Manager Code (CIV or MIL) 16 TSPSITE Char 10 68 $TSPSITE. TSP Site (regardless of age) 17 LEGDDSCD Char 2 78 $DDSFMT. DDS Code 18 PNLCATCD Char 1 80 $PNLCAT. Personnel Category Code (Duty Status) 19 MBRRELCD Char 1 81 $MBRREL. Member Relationship Code 20 DBENCAT Char 3 82 $BENCAT. Beneficiary Category 21 DMEDELG Char 1 85 $MEDELG. Medical Privlege Code 22 DSPONSVC Char 1 86 $SPONSVC. Derived Sponsor Branch of Service 23 MEDTYPE Char 1 87 $MEDTYP. Medicare Type 24 PATCAT Char 7 88 $AGGBCAT. Aggregated Beneficiary Category 25 ENRID Char 4 95 Enrollment DMISID 26 DCATCH Char 4 99 Catchment Area 27 ULOCDMIS Char 4 103 Unit DMISID 28 ENLSMPL Num 8 107 ENLSMP. ENLSMPL - Enrollment Sampling Group 29 FNSTATUS Num 8 115 FNSTATS. Final Status 30 KEYCOUNT Num 8 123 # of Key Questions Answered 31 POSTSTR Char 3 131 Post Stratification Cell 32 C00001 Num 4 134 CYN2_. 11. Are you adult responsible for child 33 C00002 Num 4 138 CPLAN1_. 11. Which hlth plan did you use most 34 C00003 Num 4 142 CENROLL. 11. In last 12 mos,# mos in a row cvrd w/Pln 35 C00004A Num 4 146 CMARK. 11. Child covered by TRICARE Prime 36 C00004B Num 4 150 CMARK. 11. Child covered by TRICARE Extra/Standard 37 C00004C Num 4 154 CMARK. 11. Child covered by Fed. EMP Health Benefit 38 C00004D Num 4 158 CMARK. 11. Child covered by Medicaid 39 C00004E Num 4 162 CMARK. 11. Child covered by Civilian HMO 40 C00004F Num 4 166 CMARK. 11. Child covered by Other Civilian Ins. 41 C00004G Num 4 170 CMARK. 11. Child covered by USFP 42 C00004H Num 4 174 CMARK. Not sure who Child covered by 43 C00004I Num 4 178 CMARK. Child did not use health plan last 12mos 44 C00005 Num 4 182 CYN2_. 11. Does child have personal Dr/Nurse 45 C00006 Num 4 186 CPROB1_. 11. How much prblem to get personal Dr/Nurse November 27, 2001

E-217


CONTENTS PROCEDURE

# Variable Type Len Pos Format Informat Label --------------------------------------------------------------------------------------------- 46 C00007 Num 4 190 COFTN1_. 11. Talk about feeling/growing/behaving 47 C00008 Num 4 194 CRATE1_. 11. Rating of childs personal Dr/Nurse 48 C00009 Num 4 198 CYN3_. 11. Does child have primary care manager 49 C00010 Num 4 202 CYN2_. 11. Know name of childs Primary care mgr 50 C00011 Num 4 206 CPROB2_. 11. In last 12 mos how much prblm to see PCM 51 C00012 Num 4 210 CWORK. 11. Is primary care mgr military or civilian 52 C00013 Num 4 214 CYN2_. 11. Did you think child needed to see spclst 53 C00014 Num 4 218 CPROB3_. 11. How much prblm to get referral to spclst 54 C00015 Num 4 222 CYN2_. 11. In last 12 mos did child see specialist 55 C00016 Num 4 226 CRATE2_. 11. Rating of specialist seen most often 56 C00017 Num 4 230 CYN4_. 11. Specialist same as personal Dr 57 C00018 Num 4 234 CYN2_. 11. Call during reg. Hrs to get help/advice 58 C00019 Num 4 238 COFTN2_. 11. Called during reg Hrs did you get hlp 59 C00020 Num 4 242 CYN2_. 11. Make appt for regular/routine hlthcre 60 C00021 Num 4 246 COFTN3_. 11. How oftn get appt for care soon as wnted 61 C00022 Num 4 250 CDAYS1_. 11. Wait btwn mking appt and seeing provider 62 C00023 Num 4 254 CYN2_. 11. Have illness/injury need care right away 63 C00024 Num 4 258 COFTN4_. 11. Get needed care as soon as wanted 64 C00025 Num 4 262 CDAYS2_. 11. Wait btwn trying to & seeing provider 65 C00026 Num 4 266 CYN2_. 11. Appointment for well-patient care 66 C00027 Num 4 270 COFTN5_. 11. Get appt for well-patient care 67 C00028 Num 4 274 CLONG. 11. Wait to see provider for well-patnt care 68 C00029 Num 4 278 CTIMESA. 11. Times to ER 69 C00030 Num 4 282 CDOCCLIN. 11. Times to Dr office/Clinic (excluding ER) 70 C00031 Num 4 286 CPROB4_. 11. Problem to get necessary care 71 C00032 Num 4 290 CPROB4_. 11. Problem wait for approval 72 C00033 Num 4 294 COFTN6_. 11. How oftn wait >15 mins 73 C00034 Num 4 298 COFTN6_. 11. How oftn staff treat w/courtesy &respect 74 C00035 Num 4 302 COFTN6_. 11. How oftn were staff helpful 75 C00036 Num 4 306 COFTN6_. 11. How oftn did staff listen carefully 76 C00037 Num 4 310 COFTN6_. 11. How oftn did staff explain things to you 77 C00038 Num 4 314 COFTN6_. 11. How oftn staff respect what had to say 78 C00039 Num 4 318 CYN2_. 11. Child old enough to talk to Dr 79 C00040 Num 4 322 COFTN7_. 11. Dr explain in way for child to undrstnd 80 C00041 Num 4 326 COFTN6_. 11. How oftn spend enough time w/child 81 C00042 Num 4 330 CRATE3_. 11. Rating of childs healthcare 82 C00043 Num 4 334 CTYPE. 11. Type of facility child used most often 83 C00044 Num 4 338 CYN1_. 11. Send in any claims 84 C00045 Num 4 342 COFTN8_. 11. Handle claim in reasonable time 85 C00046 Num 4 346 COFTN8_. 11. Handle claim correctly 86 C00047 Num 4 350 COFTN8_. 11. Plan make clear how much to pay 87 C00048 Num 4 354 CYN2_. 11. Look for info/written material 88 C00049 Num 4 358 CPROB5_. 11. Find/understand info in written material 89 C00050 Num 4 362 CYN2_. 11. Call customer service to get info 90 C00051 Num 4 366 CPROB6_. 11. Problem get help when call customer svc 91 C00052 Num 4 370 CYN2_. 11. Called/written plan with complaint 92 C00053 Num 4 374 CSOLVE. 11. How long to resolve complaint November 27, 2001

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# Variable Type Len Pos Format Informat Label --------------------------------------------------------------------------------------------- 93 C00054 Num 4 378 CYN5_. 11. Complaint/problem settled to satisfction 94 C00055 Num 4 382 CYN2_. 11. Experience with paperwork 95 C00056 Num 4 386 CPROB7_. 11. Problem with paperwork 96 C00057 Num 4 390 CRATE4_. 11. Rating of exprience with child hlth plan 97 C00058 Num 4 394 CHEALTH. 11. Rate child overall health 98 C00059 Num 4 398 CYN2_. 11. Child use medicine prescribed by Dr 99 C00060 Num 4 402 CYN2_. 11. Medicine b/c medical,behavioral,other 100 C00061 Num 4 406 CYN2_. 11. Medicine b/c cndtn expected last>=12 mos 101 C00062 Num 4 410 CYN2_. 11. Mre medical,mntl,edcution svcs thn usual 102 C00063 Num 4 414 CYN2_. 11. Use svcs b/c medical, behavioral, oth 103 C00064 Num 4 418 CYN2_. 11. Svcs b/c condition expected last>=12 mos 104 C00065 Num 4 422 CYN2_. 11. Limited/prevented in ability 105 C00066 Num 4 426 CYN2_. 11. Limited b/c medical, behavioral, other 106 C00067 Num 4 430 CYN2_. 11. Limited b/c condition expected last>=1yr 107 C00068 Num 4 434 CYN2_. 11. Get special therapy 108 C00069 Num 4 438 CYN2_. 11. Therapy b/c medical, behavioral, other 109 C00070 Num 4 442 CYN2_. 11. Therapy b/c condition expected last>=1yr 110 C00071 Num 4 446 CYN2_. 11. Problem for which gets trtmnt/counseling 111 C00072 Num 4 450 CYN2_. 11. Trtmnt/counseling b/c conditn last>=1yr 112 C00073 Num 4 454 CPREVENT. 11. Last time routine preventive care appt 113 C00074 Num 4 458 CAGE1_. 11. Childs age now 114 C00075 Num 4 462 CYN1_. 11. Child recd all immunizations 115 C00076A Num 4 466 CVACCINE. 11. # times child recd Dtap,DT,DTP 116 C00076B Num 4 470 CVACCINE. 11. # times child recd MMR 117 C00076C Num 4 474 CVACCINE. 11. # times child recd IPV or OPV 118 C00076D Num 4 478 CVACCINE. 11. # times child recd Hib 119 C00076E Num 4 482 CVACCINE. 11. # times child recd HepB 120 C00076F Num 4 486 CVACCINE. 11. # times child recd Varicella 121 C00077A Num 4 490 CMARK. 11. Talk about growth/development 122 C00077B Num 4 494 CMARK. 11. Talk about behaviors to expect 123 C00077C Num 4 498 CMARK. 11. Talk about dress/bathe/feed child 124 C00077D Num 4 502 CMARK. 11. Talk about help child grow/learn 125 C00077E Num 4 506 CMARK. 11. Talk about tlking/reading/plying w/child 126 C00077F Num 4 510 CMARK. 11. Talk about keep child from injured 127 C00077G Num 4 518 CMARK. 11. Talk about make house safe 128 C00077H Num 4 514 CMARK. 11. Talk about make car safe 129 C00078 Num 4 522 CSEX. 11. Is child male or female 130 C00079 Num 4 526 CHISP. 11. Is child Hispanic/Latino 131 C00080A Num 4 530 CMARK. 11. Child race:white 132 C00080B Num 4 534 CMARK. 11. Child race:Black 133 C00080C Num 4 538 CMARK. 11. Child race:Asian 134 C00080D Num 4 542 CMARK. 11. Child race:Native Hawaiian/Pacific Islnd 135 C00080E Num 4 546 CMARK. 11. Child race:Am. Indian/Alaskan 136 C00081 Num 4 550 CAGE2_. 11. Your age now 137 C00082 Num 4 554 CSEX. 11. Are you male or female 138 C00083 Num 4 558 CRELEDU. 11. highest grade/level you completed 139 C00084 Num 4 562 CRELATE. 11. How related to child November 27, 2001

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CONTENTS PROCEDURE

# Variable Type Len Pos Format Informat Label --------------------------------------------------------------------------------------------- 140 FLAG_FIN Char 4 566 $FINAL. $5. Final Disposition 141 DUPFLAG Char 3 570 Multiple Response Indicator 142 N2 Num 4 573 Coding Scheme Note 2 143 N3 Num 4 577 Coding Scheme Note 3 144 N4 Num 4 581 Coding Scheme Note 4 145 N5 Num 4 585 Coding Scheme Note 5 146 N6 Num 8 589 Coding Scheme Note 6 147 N7 Num 4 597 Coding Scheme Note 7 148 N8 Num 4 601 Coding scheme Note 8 149 N9 Num 4 605 Coding scheme Note 9 150 N10 Num 4 609 Coding Scheme Note 10 151 N11 Num 4 613 Coding Scheme Note 11 152 N12 Num 4 617 Coding Scheme Note 12 153 N13 Num 4 621 Coding Scheme Note 13 154 N14 Num 4 625 Coding Scheme Note 14 155 N15 Num 4 629 Coding Scheme Note 15 156 N16 Num 4 633 Coding Scheme Note 16 157 N17 Num 4 637 Coding Scheme Note 17 158 N18 Num 4 641 Coding Scheme Note 18 159 N19 Num 4 645 Coding Scheme Note 19 160 N20 Num 4 649 Coding Scheme Note 20 161 N21 Num 4 653 FORM. Coding Scheme Note 21 162 N22 Num 4 657 FORM. Coding Scheme Note 22 163 N23 Num 4 661 FORM. Coding Scheme Note 23 164 N24 Num 4 665 FORM. Coding Scheme Note 24 165 N25 Num 4 669 FORM. Coding Scheme Note 25 166 N26 Num 4 673 FORM. Coding Scheme Note 26 167 N27 Num 4 677 FORM. Coding Scheme Note 27 168 N28 Num 4 681 FORM. Coding Scheme Note 28 169 N29 Num 4 685 FORM. Coding Scheme Note 29 170 N30 Num 4 689 FORM. Coding Scheme Note 30 171 MISS_1 Num 8 693 HAMISS. Count of: Violates Skip Pattern 172 MISS_4 Num 8 701 HAMISS. Count of: Incomplete grid error 173 MISS_5 Num 8 709 HAMISS. Count of: Dont know or not sure 174 MISS_6 Num 8 717 HAMISS. Count of: Not applicable - valid skip 175 MISS_7 Num 8 725 HAMISS. Count of: Out-of-range error 176 MISS_8 Num 8 733 HAMISS. Count of: Multiple response error 177 MISS_9 Num 8 741 HAMISS. Count of: No response - invalid skip 178 MISS_TOT Num 8 749 HAMISS. Total number of missing responses 179 CONUS Num 3 757 CONUSMHS. CONUS - CONUS/OCONUS Indicator 180 XENRLLMT Num 8 760 ENROLL. Enrollment in TRICARE Prime 181 XENR_PCM Num 8 768 PCM. Enrollment by PCM type 182 XINS_COV Num 8 776 INSURE. Insurance Coverage 183 XBNFGRP Num 8 784 XBGC_S. Constructed Beneficiary Group 184 KMILWAT1 Num 8 792 HAYNN. Wait <4 wks for well patient visit-Mil 185 KCIVWAT1 Num 8 800 HAYNN. Wait <4 wks for well patient visit-Civ 186 KMILOFFC Num 8 808 HAYNN. Office wait of 15 min or more-Mil November 27, 2001

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CONTENTS PROCEDURE

# Variable Type Len Pos Format Informat Label --------------------------------------------------------------------------------------------- 187 KCIVOFFC Num 8 816 HAYNN. Office wait of 15 min or more-Civ 188 KBGPRB1 Num 8 824 HAYNN. Big problem getting referrals to spclst 189 KBGPRB2 Num 8 832 HAYNN. Big problem getting neccessary care 190 KMILOP Num 8 840 CTIMES. Outpatient visits to Military facility 191 KCIVOP Num 8 848 CTIMES. Outpatient visits to Civilian facility 192 KCIVINS Num 8 856 HAYNN2_. Beneficiary covered by civilian insuranc 193 BWT Num 8 864 BWT - Basic Sampling Weight 194 POP Num 8 872 DEERS population by CELLNAME for weights 195 WRWT Num 8 880 Final Weight 196 WRWT1 Num 8 888 Replicated/JackKnife Weight 1 197 WRWT2 Num 8 896 Replicated/JackKnife Weight 2 198 WRWT3 Num 8 904 Replicated/JackKnife Weight 3 199 WRWT4 Num 8 912 Replicated/JackKnife Weight 4 200 WRWT5 Num 8 920 Replicated/JackKnife Weight 5 201 WRWT6 Num 8 928 Replicated/JackKnife Weight 6 202 WRWT7 Num 8 936 Replicated/JackKnife Weight 7 203 WRWT8 Num 8 944 Replicated/JackKnife Weight 8 204 WRWT9 Num 8 952 Replicated/JackKnife Weight 9 205 WRWT10 Num 8 960 Replicated/JackKnife Weight 10 206 WRWT11 Num 8 968 Replicated/JackKnife Weight 11 207 WRWT12 Num 8 976 Replicated/JackKnife Weight 12 208 WRWT13 Num 8 984 Replicated/JackKnife Weight 13 209 WRWT14 Num 8 992 Replicated/JackKnife Weight 14 210 WRWT15 Num 8 1000 Replicated/JackKnife Weight 15 211 WRWT16 Num 8 1008 Replicated/JackKnife Weight 16 212 WRWT17 Num 8 1016 Replicated/JackKnife Weight 17 213 WRWT18 Num 8 1024 Replicated/JackKnife Weight 18 214 WRWT19 Num 8 1032 Replicated/JackKnife Weight 19 215 WRWT20 Num 8 1040 Replicated/JackKnife Weight 20 216 WRWT21 Num 8 1048 Replicated/JackKnife Weight 21 217 WRWT22 Num 8 1056 Replicated/JackKnife Weight 22 218 WRWT23 Num 8 1064 Replicated/JackKnife Weight 23 219 WRWT24 Num 8 1072 Replicated/JackKnife Weight 24 220 WRWT25 Num 8 1080 Replicated/JackKnife Weight 25 221 WRWT26 Num 8 1088 Replicated/JackKnife Weight 26 222 WRWT27 Num 8 1096 Replicated/JackKnife Weight 27 223 WRWT28 Num 8 1104 Replicated/JackKnife Weight 28 224 WRWT29 Num 8 1112 Replicated/JackKnife Weight 29 225 WRWT30 Num 8 1120 Replicated/JackKnife Weight 30 226 WRWT31 Num 8 1128 Replicated/JackKnife Weight 31 227 WRWT32 Num 8 1136 Replicated/JackKnife Weight 32 228 WRWT33 Num 8 1144 Replicated/JackKnife Weight 33 229 WRWT34 Num 8 1152 Replicated/JackKnife Weight 34 230 WRWT35 Num 8 1160 Replicated/JackKnife Weight 35 231 WRWT36 Num 8 1168 Replicated/JackKnife Weight 36 232 WRWT37 Num 8 1176 Replicated/JackKnife Weight 37 233 WRWT38 Num 8 1184 Replicated/JackKnife Weight 38 November 27, 2001

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CONTENTS PROCEDURE

# Variable Type Len Pos Format Informat Label --------------------------------------------------------------------------------------------- 234 WRWT39 Num 8 1192 Replicated/JackKnife Weight 39 235 WRWT40 Num 8 1200 Replicated/JackKnife Weight 40 236 WRWT41 Num 8 1208 Replicated/JackKnife Weight 41 237 WRWT42 Num 8 1216 Replicated/JackKnife Weight 42 238 WRWT43 Num 8 1224 Replicated/JackKnife Weight 43 239 WRWT44 Num 8 1232 Replicated/JackKnife Weight 44 240 WRWT45 Num 8 1240 Replicated/JackKnife Weight 45 241 WRWT46 Num 8 1248 Replicated/JackKnife Weight 46 242 WRWT47 Num 8 1256 Replicated/JackKnife Weight 47 243 WRWT48 Num 8 1264 Replicated/JackKnife Weight 48 244 WRWT49 Num 8 1272 Replicated/JackKnife Weight 49 245 WRWT50 Num 8 1280 Replicated/JackKnife Weight 50 246 WRWT51 Num 8 1288 Replicated/JackKnife Weight 51 247 WRWT52 Num 8 1296 Replicated/JackKnife Weight 52 248 WRWT53 Num 8 1304 Replicated/JackKnife Weight 53 249 WRWT54 Num 8 1312 Replicated/JackKnife Weight 54 250 WRWT55 Num 8 1320 Replicated/JackKnife Weight 55 251 WRWT56 Num 8 1328 Replicated/JackKnife Weight 56 252 WRWT57 Num 8 1336 Replicated/JackKnife Weight 57 253 WRWT58 Num 8 1344 Replicated/JackKnife Weight 58 254 WRWT59 Num 8 1352 Replicated/JackKnife Weight 59 255 WRWT60 Num 8 1360 Replicated/JackKnife Weight 60 November 27, 2001

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