coding closed questions training session 5 gap toolkit 5 training in basic drug abuse data...
TRANSCRIPT
![Page 1: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/1.jpg)
Codingclosed questions
Training session 5
GAP Toolkit 5 Training in basic drug abuse data management and analysis
![Page 2: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/2.jpg)
Objectives
• To establish a set of practical coding rules for closed questions • To explain the importance of assigning numbers to
characteristics• To construct a framework for recording missing values• To introduce identification numbers as a method of ensuring the
anonymity of respondents, while maintaining a link between files and questionnaires
![Page 3: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/3.jpg)
Components of a data file
• Cases or observations• Variables• Values
![Page 4: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/4.jpg)
Coding
• The identification of the possible values of a variable and the assignment of numbers to those values
• The numbers, representing the values, are stored in a data file
![Page 5: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/5.jpg)
Closed questions/categorical variables
• A limited number of values• The values are mutually exclusive• The values are collectively exhaustive• Code by assigning a number to each value
![Page 6: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/6.jpg)
Example
• Coding gender• Possible values: male; female• Coding scheme: 1 = Male; 2 = Female
![Page 7: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/7.jpg)
Why numbers?
• Efficient use of computers• Quicker to enter• Not subject to spelling mistakes
![Page 8: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/8.jpg)
Why numbers?
• Some statisticians define measurement as necessarily resulting in numbers
• “To measure a property means to assign numbers to units as a way of representing that property.”
(D. S. Moore, Statistics: Concepts and Controversies, 2nd ed. (New York, W. H. Freeman Press, 1985)).
![Page 9: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/9.jpg)
Pre-code
• Coding takes place before the questionnaire is delivered• The possible responses to a question are anticipated• The coding appears on the questionnaire
![Page 10: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/10.jpg)
Coding rules
• Codes must be:– Mutually exclusive– Collectively exhaustive– Consistent across variables
(J. Fielding, “Coding and managing data”, Researching Social Life, N. Gilbert, ed. (London, Sage Publications, 1993) and D. De Vaus, Surveys in Social Research (London, Routledge, 2002)).
![Page 11: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/11.jpg)
Continuous variables
• Do not generally require coding as:– They are already numerical– There is a potentially infinite number of categories
![Page 12: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/12.jpg)
Coding in SPSS
• The Values column in Variable View is used to implement coding in SPSS
• Numbers are allocated to each of the categories of a variable
![Page 13: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/13.jpg)
Example: coding Drug
• In data file Ex1.sav, a variable called Drug was defined as a string variable and a number of drugs were entered
Drug
1 Heroin
2 Alcohol
3 Hashish
4 Bhang
5 Heroin
6 Hashish
Total N 6
Case summariesa
a Limited to first 100 cases.
![Page 14: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/14.jpg)
Coding Drug
• Decide on a set of numeric labels for the different categories, in this case drugs:– 1 = Heroin– 2 = Alcohol– 3 = Hashish– 4 = Bhang
![Page 15: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/15.jpg)
Coding Drug
• Create a new variable Drug2:type = numeric; width = 2; decimals = 0;label = Drug Coded
• Click on the Values column and then on the three dots that appear to the right of the Values box to generate the following dialogue box:
![Page 16: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/16.jpg)
Click to register code
![Page 17: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/17.jpg)
![Page 18: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/18.jpg)
Frequency Percentage Valid percentage
Cumulative percentage
Valid Heroin 2 33.3 33.3 33.3
Alcohol 2 33.3 33.3 66.7
Hashish 1 16.7 16.7 83.3
Bhang 1 16.7 16.7 100.0
Total 6 100.0 100.0
Drug Coded
Frequency count for Drug Coded:
![Page 19: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/19.jpg)
Note
• Coding data does not change the level of measurement• The level of measurement is a guide to the selection of
appropriate statistics
![Page 20: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/20.jpg)
SPSS
• Value labels can be assigned to numeric variables and string variables of eight or fewer characters
• By default, SPSS sets all numeric variables to Scale variables
![Page 21: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/21.jpg)
Exercise: coding
ID Drug Age ConditionDAP1-007 Mandrax 27 RecoveredDAP1-008 Mandrax 21 RelapsedDAP1-009 Alcohol 45 RecoveredDAP1-010 Hashish 52 RelapsedDAP1-011 Mandrax 22 RelapsedDAP1-012 Alcohol 28 Relapsed
![Page 22: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/22.jpg)
Frequency count of Drug
Frequency Percentage Valid percentage
Cumulative percentage
Valid Alcohol 3 25.0 25.0 25.0
Bhang 1 8.3 8.3 33.3
Hashish 3 25.0 25.0 58.3
Heroin 2 16.7 16.7 75.0
Mandrax 3 25.0 25.0 100.0
Total 12 100.0 100.0
Drug
![Page 23: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/23.jpg)
Frequency count of Condition
Frequency Percentage Valid Percentage
Cumulative percentage
Valid Recovered 5 41.7 41.7 41.7
Relapsed 7 58.3 58.3 100.0
Total 12 100.0 100.0
Condition Coded
![Page 24: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/24.jpg)
Missing values
![Page 25: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/25.jpg)
Missing values: causes
• The question is not applicable• The respondent does not know• The respondent refuses to answer• No response is marked on the questionnaire (i.e., truly
missing and there is no clue why)(De Vaus, 2002)
![Page 26: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/26.jpg)
Coding missing values
• Use codes outside of the range of common values:– e.g., 9, 99, -99, 999
• If possible, retain the same codes for the various missing options for all variables
• The default missing value in SPSS is a full stop . and is called the “system’s missing value”
![Page 27: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/27.jpg)
SPSS: missing values
• Part of the variable definition• Variable View: Missing column
– Click on the Missing cell in the row defining the variable– Click on the three buttons that appear to the right of the
Missing cell and the following dialogue box will appear:
![Page 28: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/28.jpg)
![Page 29: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/29.jpg)
Exercise
• Three additional observations are obtained for Ex1.sav:– DAP1-0013; Alcohol; 39; ------------– DAP1-0014; Hashish; --; Recovered– DAP1-0015; ---------; 16; Relapsed
• Code necessary missing values for the variables• Run a frequency count on Drug and Condition,
comparing percentage and valid percentage
![Page 30: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/30.jpg)
Identification numbers
![Page 31: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/31.jpg)
ID numbers: purpose
• An ID number:– Ensures anonymity– Links a row in the data file to a physical questionnaire
![Page 32: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/32.jpg)
ID numbers: characteristics
• A unique identifier• Sometimes contains information in a compound form
![Page 33: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/33.jpg)
Example
• DAP1-001, DAP1-002, … :– DAP is short for Drug Assessment Programme– 001, 002 are consecutive numbers that uniquely identify each
questionnaire or respondent – There must be at most 999 respondents, as space has only
been made available for 999 unique ID numbers
![Page 34: Coding closed questions Training session 5 GAP Toolkit 5 Training in basic drug abuse data management and analysis](https://reader035.vdocuments.us/reader035/viewer/2022062407/56649e255503460f94b1410b/html5/thumbnails/34.jpg)
Summary
• Coding closed questions• Value labels• Frequency counts• Missing values• ID numbers