pushing the edge of the contemporary cognitive (chc) theory: new directions for psychologists

Pushing the edge of the contemporary cognitive (CHC) theory: New directions for

psychologists

Kevin S. McGrew, PhD

Woodcock-Muñoz Foundation

16th Annual APS College of Clinical Neuropsychologists Conference

From East to West: New directions in Neuropsychology

30 September - 2 October 2010

Notre Dame University, Fremantle, Western Australia

Or…..what an inquisitive applied intelligence scholar/psychometrician constructed/discovered

from playing almost a decade in his data, literature, and theoretical sandbox

“Intelligent” testing and interpretationrequires…knowing thy instruments

Error variance (reliability)

Uniqueness (specificity)

g loading

External criterion relevance

Information processing & stimulus/response characteristics

Ability domain cohesion

Degree of cultural loading

Degree of linguistic demand

Metric scale

Degree of cognitive complexityCHC Ability factor classifications

Neuropsych. interpretation

http://www.remotecentral.com/dvd/romance1.jpg

“ If you give a monkey a stradivarius violin and you get bad music……..you don’t

blame the violin”

McGrew (circa 1986)

Three things (or major steps) completed that have resulted in the intelligence

model(s) to be presented today

Things 1 and 2:Will be covered quickly to provide context and

background for primary content of today – Thing 3

“It is notable that there is a gap between neuropsychological measures and evolving

conceptualizations of intelligence. That is, for as seemingly related as the instruments and concepts are, they have strikingly different

historical backgrounds.”

(Hoelzle, 2008)

Psychometric vs. neuropsychological conception/model assessment gap

• NP measures traditionally selected on ability to differentiate between neurological and normal conditions---psychometric

frameworks derived with factor analytic techniques to synthesize theories that were similarly derived

• Singular concept of intelligence (g) has had minimal clinical utility in neuropsychological assessment

Psychometric vs. neuropsychological assessment gap: Select reasons why (Hoelzle, 2008)

• NP assessment has been traditionally non-theoretical---popular models of

intelligence and cognitive abilities have been derived via statistical procedures

Vertical factor analysis (trait) model

Gf Gc Glr G..GsmGv etcAttn

Psychometric approaches have had primary (but not sole) focus/goal on internal/structural validity within each construct

domain --- Vertical models

Horizontal multiple regression (aptitude/functional/pragmatic) model

Gf Gc Glr G..GsmGv etcAttn

Criterion DVs

TBI ?

Brain Area/function

Neuropsychological approaches have had primary (but not sole) focus/goal on external/predictive (Dx) validity –

Horizontal models

Result has been many NP measures are mixture measures of multiple CHC domain abilities (which abilities and in

what amount [weighting] best predict criterion variables?)

My primary goal

Present a different (yet compatible value-added) psychometric theory of intelligence perspective for thinking about testing

cognitive abilities

Importance Of Classification Taxonomies In All Sciences

Classification is arguably one of the most central and generic of all our conceptual exercises…without

classification, there could be no advanced conceptualization, reasoning, language, data analysis, or

for that matter, social science research (K.D. Bailey, 1994).

A specialized science of classification of empirical entities known as taxonomy (Bailey, 1994; Prentky, 1994)

is ubiquitous in all fields of study because it guides our search for information or truth.

Unique abilities not shared in common with other CHC factor indicators (specificity)

Reliable variance (reliability)

Error variance-individual/situational variables (e.g., distractibility)-item variables (e.g., item sampling and item gradients; test floor and ceiling)-examiner variables (e.g., rapport, scoring and administration errors)-testing environment variables (e.g., noise, comfort)

We have been searching for an empirically/theoretically-based cognitive taxonomy to interpret the reliable variance of cognitive tests

?

The CHC Timeline Project (and detailed information re: CHC theory/model) can be found at IQ’s Corner blog

www.iqscorner.com

The Cattell-Horn-Carroll (CHC) theory of cognitiveabilities is the contemporary consensus

psychometric model of the structure of human intelligence

PMA1

T2 T3 T4 T5 T6 T7 T8 T9T1 T12T10 T11

PMA2 PMA3 PMA4 …etc

…etc

G1 G2 G3 …etc

T2 T3 T4 T5 T6 T7 T8 T9T1 T12T10 T11

g

(1a) Spearman’s general Factor model

PMA1

T2 T3 T4 T5 T6 T7 T8 T9T1 T12T10 T11


…etc

(1b) Thurston’s Multiple Factor (Primary Mental Abilities) Model

PMA1

T2 T3 T4 T5 T6 T7 T8 T9T1 T12T10 T11

…etc

…etc

…etc

PMA2 PMA3 PMA4

G2G1

g

Arrows from g to each test(rectangle) have been omitted for readability

Stratum I

Stratum II

Stratum III

(1d) Carroll’s Schmid-Leiman Hierarchical Three-Stratum Model(1c) Cattell-Horn Gf-Gc Hierarchical Model

PMA1

T2 T3 T4 T5 T6 T7 T8 T9T1 T12T10 T11


…etc

G1 G2 G3

…etc

g ?

(1e) Consensus Cattell-Horn-Carroll Hierarchical Three-Stratum Model

Figure 1: Major stages in the evolution of psychometric theories from Spearman’s g to Cattell-Horn-Carroll (CHC) theory

Note: Circles representlatent factors. Squares represent manifest measures (tests; T1..). Single-headed path arrows designate factor loadings. Double headed arrows designate latent factor correlations

Stratum I

Stratum II

Stratum III

CHC theory has entered the mainstream neuropsychological assessment literature

THE SCOPE OF CARROLL’S FACTOR ANALYTIC REVIEW

• Reviewed factor analytic research of the past 50-60 years

• Includes nearly all of the more important and classic factor analytic investigations

• Started with 1,500 references• Final pool of 461 data sets that meet specific

criteria• Reanalyzed all or nearly all of the data sets• Used exploratory methods in order to “let the

data speak for themselves”

Richard Snow (1993): “John Carroll has done a magnificent thing. He has reviewed and reanalyzed the world’s literature on individual differences in cognitive abilities…no one else could have done it… it defines the taxonomy of cognitive differential psychology for many years to come.”

Burns (1994): Carroll’s book “is simply the finest work of research and scholarship I have read and is destined to be the classic study and reference work on human abilities for decades to come” (p. 35). John Horn (1998): A “tour de force summary and integration” that is the “definitive foundation for current theory” (p. 58). Horn compared Carroll’s summary to “Mendelyev’s first presentation of a periodic table of elements in chemistry” (p. 58).

Arthur Jensen (2004): “…on my first reading this tome, in 1993, I was reminded of the conductor Hans von Bülow’s exclamation on first reading the full orchestral score of Wagner’s Die Meistersinger, ‘‘It’s impossible, but there it is!’’

“Carroll’s magnum opus thus distills and synthesizes the results of a century of factor analyses of mental tests. It is virtually the grand finale of the era of psychometric description and taxonomy of human cognitive abilities. It is unlikely that his monumental feat will ever be attempted again by anyone, or that it could be much improved on. It will long be the key reference point and a solid foundation for the explanatory era of differential psychology that we now see burgeoning in genetics and the brain sciences” (p. 5).

The verdict is unanimous re: the importance of Carroll’s (1993) work

Contemporary psychometric research has converged on the Cattell-Horn-Carroll (CHC) theory of cognitive abilities as the

consensus working taxonomy of human intelligence

McGrew, K. (2009). Editorial: CHC theory and the human cognitive abilities project: Standing on the shoulders of the giants of psychometric intelligence research, Intelligence, 37, 1-10.

Because the Carroll model is largely consistent with the model originally proposed by Cattell (1971), McGrew (2009) has proposed an integration of the two models which he calls the Cattell-Horn-Carroll (C-H-C) Integration

model….Because of the inclusiveness of this model, it is becoming the standard typology for human ability. It is certainly the culmination of

exploratory factor analysis.

The Science of Intelligence (Doug Detterman, 2010; book manuscript in preparation)

PMA1

T2 T3 T4 T5 T6 T7 T8 T9T1 T12T10 T11


…etc

G1 G2 G3…etc

g ?


CHC as the consensus psychometric model of

intelligence

“The Cattell–Horn–Carroll (CHC) theory of cognitive abilities is the best validated model of human

cognitive abilities”

[Ackerman, P. L. & Lohman D. F. (2006). Individual differences in cognitive functions. In P. A. Alexander, P. Winne (Eds.), Handbook of educational

psychology, 2nd edition (pp. 139-161). Mahwah, NJ: Erlbaum.]

PMA1

T2 T3 T4 T5 T6 T7 T8 T9T1 T12T10 T11


…etc

G1 G2 G3

…etc

g ?



intelligence

A significant number of Australian intelligence scholars have framed (and/or continue to frame) their research as per the extended Gf-Gc (aka. CHC) model of intelligence. Many have made foundational contributions to building

the model.

N. R. BurnsT. Nettlebeck

L. StankovR. RobertsS. Bowden

PMA1

T2 T3 T4 T5 T6 T7 T8 T9T1 T12T10 T11


…etc

G1 G2 G3

…etc

g ?



intelligence

Importance Of Classification Taxonomies In All Sciences

Classification is arguably one of the most central and generic of all our conceptual exercises…without

classification, there could be no advanced conceptualization, reasoning, language, data analysis, or

for that matter, social science research (K.D. Bailey, 1994).

A specialized science of classification of empirical entities known as taxonomy (Bailey, 1994; Prentky, 1994)

is ubiquitous in all fields of study because it guides our search for information or truth.

Gf

Broad

g General

RG

IRQ RE

RPNarrow

CHC theory classifies abilities according to three levels or strata

RG = Gen Sequential (deductive) Reasoning

I = Induction

RQ = Quantitative Reasoning

RP = Piagetian Reasoning

RE = Speed of Reasoning

All CHC narrow abilities and their definitions can be found at www.IAPsych.com

g

Gf GqGcSARGsm Gv Ga

TSRGlm Gs CDS Grw

Gkn Gh Gk Go

Gf Gc Gy Gv Gu Gr Gs Gt

Gp Gps

A. Carroll Three-Stratum Model

B. Cattell-Horn Extended Gf-Gc Model

D. Tentatively identified Stratum II (broad) domains

Carroll and Cattell-Horn Broad Ability Correspondence (vertically-aligned ovals represent similar broad domains)

Gf GqGc Gsm Gv Ga Glr Gs Gt Grw

C. Cattell-Horn-Carroll (CHC) Integrated Model

g

Stratum III (general)

Stratum II (broad)

80+ Stratum I (narrow) abilities have been identified under the Stratum II broad abilities. They

are not listed here due to space limitations(see Table 1)

Gf Fluid reasoning Gkn General (domain-specific) knowledgeGc Comprehension-knowledge Gh Tactile abilitiesGsm Short-term memory Gk Kinesthetic abilitiesGv Visual processing Go Olfactory abilitiesGa Auditory processing Gp Psychomotor abilitiesGlr Long-term storage and retrieval Gps Psychomotor speedGs Cognitive processing speedGt Decision and reaction speed (see Table 1 for definitions)Grw Reading and writingGq Quantitative knowledge

CHC Broad (Stratum II) Ability Domains

(Missing g-to-broad ability arrows acknowledges that Carroll and Cattell-Horn disagreed on the validity of the general factor)

...most disciplines have a common set of terms and definitions (i.e., a standard nomenclature) that facilitates communication among professionals and guards against

misinterpretations. In chemistry, this standard nomenclature is reflected in the ‘Table of Periodic Elements’. Carroll

(1993a) has provided an analogous table for intelligence…..

(Flanagan & McGrew, 1998)




CHC Theory is the best available empirically and theoretically sound cognitive ability taxonomy available today

g

Gf

Gc

Gv

Gsm

Glr

Ga

Gs

This is where the field of psychometric intellectual assessment is at..and a bandwagon has formed




g

Gf

Induction (I)

General Seq. Reasoning (RG)

Quantitative Reasoning (RQ)

Speed ofReasoning (RE)

Gc

Listening Ability (LS)

General Information (K0)

Lang.Develpmt (LD) (LD)

LexicalKnowledge (VL)

Secondary ability

Primary ability

Published WJ III CHC model (McGrew & Woodcock,

2001

CFA analysis of 50+ cognitive

and achievement

tests

GcGq Ga GsmGlr GvGf

g

Grw Gs

.55.91.88.73.87 .88.79.82.93

First order measurement model omitted for readability purposes

Starting point

Ages 6-adult CFA Broad CHC Model in WJ III Technical Manual(McGrew & Woodcock, 2001)

Deconstruction: The validated/published WJ III CHC

structure was “torn down”

Psychologists need a healthy degree of positive skepticism

Reconstruction: New structural models specified based on insights

from large variety of statistical analysis of the WJ III norm data since

2001.

Stage (Thing 2) approach

Theoretical considerations (Berlin BIS model; dual-processing cognitive models; etc.) also served as guides during exploratory model specification.

Important caution: The final models demonstrated near identical model fit statistics (e.g., some equivalent models). Also, the large amount of exploratory model specification employed has the potential to capitalize on "random chance factors"- thus rendering statistical model evaluation comparisons useless.

The goal of these analyses were to "push the edge of the envelope" of the WJ three data via SEM-based model generation procedures. The law of parsimony was deliberately discarded.

Cross validation of proposed final models in independent samples is needed.

Variety of Exploratory Data Analyses with Variety of Datasets

Data Sets

• WJ III norm data• WJ III+ other batteries

(WISC-R; WAIS-III/WMS-III/KAIT)• WAIS-IV subtest correlations

Methods• Cluster analysis• Multidimensional scaling analysis (MDS) – 2D and

3D• Standard and Carroll EFA+CFA exploratory factor

analysis• Model-generation CFA (SEM)• CHC cognitive causal SEM models

Cluster analysis of WJ III and WJ III + other batteries (joint analysis) + other batteries

alone (WAIS-IV)

Cluster analysis is an set of exploratory (structure discovering) data analysis tools for solving classification problems. Sometimes it has been called a “poor mans” factor analysis. Its object is to sort cases (people, things, events, tests, etc) into groups, or clusters, so that the degree of association is strong between members of the same cluster and weak between members of different clusters. Each cluster thus describes, in terms of the data collected, the class to which its members belong; and this description may be abstracted through use from the particular to the general class or type.

CA often helps confirm EFA results and similar to MDS (multidimensional scaling), can spatially represent the degree of similarity of tests measuring a common dimension (dimension cohesion). Its hierarchical sequential structure is often useful in suggesting higher-order dimensions/factors.

Cluster Analysis

The strength of cluster analysis (discovering structure in data with more relaxed statistical assumptions and mathematics than data reduction methods such as exploratory factor analysis) is also one of its major limitations. CA will find groups or clusters in random data. The algorithms are designed to find any structure, even if structure is not present. As a result, the later clusters in a hierarchical approach are often “necessary evils or by products”--CA must end with one grand cluster. Thus, often in CA a point is reached where the further collapsing of meaningful groupings ceases to make substantive sense. It is important to recognize this in the resultant cluster dendogram.

Also, given the above, tests (objects, etc.) that share little in common with other measures need to be assigned to some grouping and cluster. Thus, often “loner” type tests will appear in very meaningful clusters but will not be consistent with the underlying interpretation of the grouping/cluster. Sometimes this suggests new insights regarding the test. Other times these “I’ve got to be grouped with some cluster somewhere in the process” tests are best ignored and should not interpreted as discounting the strong communality of a grouping or clustering of tests

Cluster Analysis

0.0 0.5 1.0 1.5 2.0 2.5Distances

VC

VAL

SPR

SB

CF

VM

NR

IW

AWM

DRV

GI

REF

PR

AA

AS

DS

MW

RPN

PLN

PC

LW

RDF

STR

UD

CALMF

SP

WFPSC

AP

WS

DRS

WAPV

OC

EDRV

QC

AK

SOS

SA

MN

VCL

SNP

NS

NM

CO

MS

BR

DRM

Glr-MA

GaPC

SR/Vz

Ppr

MW

MSGsm

?SR/Vz+

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Temporal Processing or Tracking /Aud. Sequential Processing

Pc

R9

NA/R4 (RAN?)Gs (cognitive)

LD/VL

K0

LS

?

Gc

RC

RQ

Gs (achievement)

Grw

Orthographic processing?

Grw (words,sent, con. disc)

Grw (phonemes)

Complex lang. processing/reasoning? Gf

Gf (language-based)

Clusters beyond this point not easily interpretable – see limitations of CA method

?

Cluster analysis (Wards method) of 50 WJ III

cognitive and achievement tests (ages

6-18; NU norms)

Kevin McGrew11-13-09

? = no apparent current CHC ability classification

Red font = CHC factors

Blue font = possible new abilities at different strata to consider

Gf (numeric-based)

© Institute for Applied Psychometrics llc 12-07-03

0.0 0.5 1.0 1.5 2.0 2.5Distances

VAL

SPAREL

SNDBLN

CONFRM

VISMAT

NUMREV

INCWRD

AWKMEM

GENINF

RETFLU

PICREC

AUDATN

ANLSYN

DECSPD

MEMWRD

RPCNAM PLAN

PAIRCN

LWIDNT

RDGFL

STYREC

UNDDIR

CALC

MTHFLU

SPELL

WRTFLU

PSGCMP

APPROB

WRTSMP

WRDATK

ORLCMP

EDIT

RDGVOC

SPLSND

SNDAWR

PICVOC

ORALVOC

VERBANL

QCCONC

AKSCI AKSOC AKHUM

MEMNAM

VISCLO

SNDPTV

NUMSER NUMMAT

CRSOUT

MEMSEN

BLKROT

[ phoneme/grapheme knowledge ]

VRC

K0

LD/VL

Gc (content facet – words & connected discourse)

LS

Grw (content facet –Language; read or written)

MA

A3/KM

RQ

Gf

Gq (content facet – numerical)

MS

PC

NA

SR/Vz

MV

Gsm

Ga

SR/Vz

Gv (content facet—visual/figural)

P

Gs (cog/process)

Gs (ach/content)

Gs System 1 (automatic) cognitive processing

g (stratum III)

Cluster analysis (Ward method) for all WJ3 tests across all ages (K. McGrew 12-7-03)

(Shading designates stratum II abilities)

System 2 (controlled) cognitive processing

Ga+Gsm (content facet–auditory)

(content facet – figural/visual)

WAIS-IV test Cluster Tree (Wards method) of WAIS-IV subtest intercorrelations

0.0 0.5 1.0 1.5Distances

BD

SI

DS

MR

VC

AR

SS

VP

IN

CD

LN

FW

CO

CA

PCM

Verbal know & comp (Gc)

Short-term & working memory (Gsm)

Fluid Reasoning (Gf)

Visual-Spatial Proc.(Gv)

Processing Speed (Gs)(rate cognitive abilities)

Level (unspeeded) cognitive abilities

General Intelligence (g) as per WAIS-IV?

© Institute for Applied Psychometrics, llc 02-05-02

Gv

Cog Fluency/ Efficiency (unspeeded)

Succ Proc/ Gsm / Temp Tracking ?

Cog Fluency/ Efficiency (speeded)

Gc

Gf/MW?

Glr

Gq/Gf

McGrew-Evans WJ III/WISC-III Cluster Analysis Interpretation Worksheet

VRBCMP

VAL

SPAREL

BLND

CONFRM

VISMAT

NUMREV

INCWRD

AWKMEM

GENINF

RETFLU

PICREC

AUDATN

ANLSYN

DECSPD

MEMWRD

RPCNAM

PLAN

STYREC

UNDDIR

CALC

APPROB

ORLCMP

QNTCON

PCSS

INFOSS

CODSS

SIMSS

PS

ARITHSS

BDSS

VOCSS

OS

COMPSS

SSSS

DSSS

BLKROTWR

MEMNAMWR

MEMSENWR

SNDPATWR

VISCLOWR

ACKNOWWR

NUREAWR Thinking Abilities /Controlled Processing

Acquired Knowledge

Cognitive Efficiency /Automatic Processing

US/UR

PC

MSP/R9

NA/R4/RAN

LDVL

MW

MA

A3

RQ

SR/VZSR

Gs

Phelps WJ III Technical ManualValidity sample – n=150 grade 3-5


0 1 2 3 4Distances

WJR Analysis-Synthesis

WJR Concept Formation

KAIT Logical Steps

KAIT Mystery Codes

WJR Picture VocabularyWJR Oral Vocabulary

KAIT Double Meanings

KAIT Definitions

KAIT Auditory Comprehension

KAIT Famous Faces

WJR Memory for WordsWJR Memory for Sentences

KAIT Memory for Block Designs

WJR Visual Closure

WJR Picture RecognitionWISC3 Object Assembly

WJR Incomplete WordsWJR Sound Blending

WJR Memory for NamesWJR Visual-Auditory Learning

KAIT Rebus LearningKAIT Rebus Learning-Delayed

KAIT Auditory Comprehension-Delayed

WJR Letter-Word IDWJR-Reading Vocabulary

WJR Visual MatchingWJR Cross Out

Gc/Grw

RG

P (Gs)

MS (Gsm)

PC (Ga)

MV

CS

I

LS/MM

MA

Glr

Gy

VL

LD

Gv

Gf

Gc

Flanagan & McGrew (1998) WJ-R/KAIT joint cluster analysis

Late Career Carroll-EFA+CFA Method (e.g., Carroll, 2003) of WJ III

Traditional EFA of WJ III at various age levels

CHC CFA (SEM) of WJ III and WJ III + other batteries (joint analysis)


VRBCMPZ

ANLSYNZ

CONFRMZ

CRSOUTZ

INCWRDZ

MEMNAMZ

MEMSENZ

MEMWRDZ

NUMREVZ

PICRECZ

BLNDZ

SPARELZ

VISCLOZ

VISMAT2Z

SNDPATZ

AUDATNZ

BLKROTZ

DECSPDZ

RETFLUZ

MTHFLUZ

RPCNAMZ

AWKMEMZ

VALZ

LWIDNTZ PSGCMPZRDGFLZ

WVOCSS

WSIMSS

WARITHSS

WINFOSS

WCOMPSS

WLNSSS

WPICCSS

WDSYSS

WBDSS

WMATRSS

WPICASS

WSYMSSS

KDEFSS

KREBLSS

KLOGSTSSKAUDCSS

KMYSCSS

KDOUBMSS

r1

r2

r3

r4

r6

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r8

r10

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r22

r9

r42r43

r44

Gc

Gsm

GrwGf

Gv

Gs

Ga

Glr

f2

f1

f9

f7

f6

f3

f5

f8

g

.70

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f10

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.69

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.90

.80

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.50

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.26

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.25

.66

.76

.64

.69

.50

.67

.67

.60.75

.67

.47

.55

.69

.30.53

.36

.60

.77

.21

.24

.59

.83

.85

.73

WMSF2SS

WMSLM2SS

WMSLM1SS

WMSVP1SS

WMSF1SS

WMSVP2SS

WMSSSSS

WMSLNSSS

WMSFP1SS

WMSFP2SS

r53

r54 r52 r51r50

r49

r48

r47

r46

r45.50

.67

.80

.54

.55

.89

.49

.70

.54

.91

.78

.36

.43

.36

.09

.26

.36

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.64

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.80

.31

.80

.22

.84

.45

.31

.35

.21

.54

.51

.57

.38

.62

.69

.51

.64

Gregg/Hoy College Sample-WJ III + WAIS-III + WMS-III(LD/Non-LD; n=200)

(McGrew et al., 2001)


VRBCMPZ

ANLSYNZ

CONFRMZ

CRSOUTZ

INCWRDZ

MEMNAMZ

MEMSENZ

MEMWRDZ

NUMREVZ

PICRECZ

BLNDZ

SPARELZ

VISCLOZ

VISMAT2Z

SNDPATZ

AUDATNZ

BLKROTZ

DECSPDZ

RETFLUZ

MTHFLUZ

RPCNAMZ

AWKMEMZ

VALZ

LWIDNTZ PSGCMPZRDGFLZ

WVOCSS

WSIMSS

WARITHSS

WINFOSS

WCOMPSS

WLNSSS

WPICCSS

WDSYSS

WBDSS

WMATRSS

WPICASS

WSYMSSS

KDEFSS

KREBLSS

KLOGSTSSKAUDCSS

KMYSCSS

KDOUBMSS

r1

r2

r3

r4

r6

r7

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r42r43

r44

Gc

Gsm

GrwGf

Gv

Gs

Ga

Glr

f2

f1

f9

f7

f6

f3

f5

f8

g

.70

.70

.89

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f10

.72

r5

.38

.45

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.22

.90

.80

.19.24

.50

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.26

.57

.25

.66

.76

.64

.69

.50

.67

.67

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.67

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.55

.69

.30.53

.36

.60

.77

.21

.24

.59

.83

.85

.73

WMSF2SS

WMSLM2SS

WMSLM1SS

WMSVP1SS

WMSF1SS

WMSVP2SS

WMSSSSS

WMSLNSSS

WMSFP1SS

WMSFP2SS

r53

r54 r52 r51r50

r49

r48

r47

r46

r45.50

.67

.80

.54

.55

.89

.49

.70

.54

.91

.78

.36

.43

.36

.09

.26

.36

.32

.64

.52.47

.80

.31

.80

.22

.84

.45

.31

.35

.21

.54

.51

.57

.38

.62

.69

.51

.64

SEM Causal Information Processing Models of WJ III

Figure 4: WJ III CHC information processing g causal model (ages 14-19)

Gf

Gv

Gs

Glr

Ga

Gc

.69

.47

.53

.78

.66

.81

.50

.69

.72

.74

.58

.40

g

.83

.95

.87

.77

.92

.49

.74

.94

.59

.88

.74

.78

.78

.78

.75

.72

.72

.80.27

.07

.82

.07

MS

MW

Memory for Names

Picture Recognition

Vis-Aud Lrng (VAL)

Del Recall-VAL

Retrieval Fluency

Numerical Reas

Concept Formation

Analysis-Synthesis

General Information

Oral Comp

Verbal Comp

Sound Blending

Sound Patterns

Incomplete Words

Block Rotation

Spatial Relations

Visual Matching

Decision Speed

Cross Out

Mem for Sentences

Mem for Words

Aud Working Mem

Numbers Reversed

76 % of g variance explained

Note: Ovals representlatent factors. Rectangles represent manifest measures (tests). Single-headed arrows to tests from ovals designate factor loadings. Single headed arrows between ovals represent causal paths (effects). Test and factor residuals omitted for readability purposes.

Cognitive Efficiency

Guttman’s Radex Theory

Ability tests can be classified by:

• Degree of cognitive complexity

• Differences in kind of content

• Differences in type of processes

Uses MDS (multidimensional scaling)

Example of MDS (Radex Model)

The closer a test is to the center of the figure, the more it is related to the underlying general dimension of the battery. Also, the center represents the most cognitively complex (i.e., have the largest number of performance components) tests.

Tests that group together are interpreted as sharing common stimulus content or cognitive processing characteristics

-3 -1 1 3

Dimension-1

-3

-1

1

3

Dim

en

sio

n-2

CA SS

CD

PCM

BD

DS

VP

COVC

SIFW

AR

LN

MRIN

Visual-spatial processing (Gv)

Processing speed (Gs)

Verbal know & comp (Gc)

Short-term memory /working memory (Gsm)

MDS (Guttman Radex model) of WAIS-IV subtest intercorrelations

Fluid reasoning

(Gf)

-3 -1 1 3

-3

-1

1

3

CA

SS

CD

PCM

BD

DS

VP

COVC

SI

FW

AR

LN

MRIN

Short-term memory /working memory (Gsm) – Cognitive

Efficiency unspeeded/memory

Processing speed (Gs) - Cognitive Efficiency speeded

Verbal know & comp (Gc) –

Acquired Knowledge or

“Product” dominant abilities?

Fluid Reasoning (Gf) and Visual-spatial processing (Gv) –

Thinking or “Process” dominant abilities?

MDS (Guttman Radex model) of WAIS-IV subtest intercorrelations

It is a common practice in MDS analysis to visually partition the MDS spatial configuration into broader dimensions and consider interpretation at a higher-order level.

The current WAIS-IV MDS revealed the following hypothesized higher-order structure

Note – similar to hand rotation of factors in early days of EFA, K. McGrew took the cross-hair lines and hand rotated them (simultaneosly) until a meaningful pattern emerged. The four-broad dimensions are interpreted as being very similar to the four cognitive domains of Woodcock’s Cognitive Performance Model (CPM) – see next two slides

-3 -2 -1 0 1 2

DIM(1)

-2

-1

0

1

2

DIM

(2)

val

SPR

VM

IW

drv

REF

AA

AS

PC

STR

SPLWS

drs

OC

EDSOS

mn

SNP

NM

MS

Gf

Gsm

glr

Ga

Gv

Gs

GcGrw

Gq

Broad CHC factor ability font key legend(based on CFA studies)

WF

DS

CAL

NR

BR

PLN

VCL

drm

PV

MF

AKGI

VCPSC

WALW

RV

SB

UDNS

APQC

CF

PR

MW

RDF

RPNAWM

CO

SA

• Thinking abilities• Process-dominant “level”

abilities• Visual-spatial/figural (low

linguistic) stimuli (Gv,Gf,Glr)• Controlled cognitive

processing

Cognitive efficiency (speeded-Gs) rate/fluency abilities• Automatic cognitive

processing

Cognitive efficiency (unspeeded-Gsm) abilities

• Automatic cognitive processing

• Acquired knowledge abilities

• Product -dominant “level” abilities

• Language (aud-linquistic) and symbolic stimuli

(Ga,Gc,Grw,Gq)• Controlled cognitive

processing

The grand “big picture model” --- probably requires a subsequent 3-D MDS analysis to see clearly….more to come

WJ III Radex Model


More process-

dominant

-3

0

2DIM

(1)

-2

0

2

DIM(2)

2

DIM(3)

VAL

SR

BL

CF

NRIW AWMRF

AA

AS

DS

MWRPN

PL

PC CA

MFWF

AP

SA

CNC

MNSPV

NSNMCO

BR

More product-

dominantMore Syste

m 1

(automatic) cognitive

processes

Note – all Gc and

Grw unspeeded tests

are omitted and are

located within

dashed area in center

VMRDF

VC

PR

Gsm

Gv

Gq

Gf

Red font = Gs

Blue font = Ga

More System 2

(controlled) cognitive

processes

More

visual-spatial

& figural

More auditory

& linguisti

c

WJ III 3-D MDS Model




g loading






Metric scale




Food for thought: Are the MDS quadrants or partitions reflecting content “facets” or a combination of content

“facets and “operations” as per the BIS model of intelligence….see next slide

Gs

Gsm + Glr (level abilities) Carroll’s Gy

Glr(fluency abilities)Gf

Note difference in term in different versions:Processing capacity defined as complex reasoning

BIS: Berlin Model of Intelligence Structure

Unveiling of preliminary new models in WJ III norm data

GcGq Ga GsmGlr GvGf

g

Grw

Gs (Gv)

Gs (Gq)

Gs (Gc)

Gs (Grw)

Gs(Cognitive speed)

.39

.82.88.71.87 .86.79.841.0

.64.55.62.59

.36

.49.54

.62

First order measurement model and other lower-order latent factors (below smallest oval latent factors) omitted for readability purposes. Thicker path arrow with bold font 1.0 parameter designates path that had to be constrained (fixed) to 1.0

Alternative Model 1

GcGq Ga GsmGlr GvGf

g

Cog. knowledge domains/systems(product/content abilities)

Lang/linguistic./symbolic abilities

Cognitive operations(process/operations/analytic/rule-

based abilities) figural-spatial, lower-linguistic abilities

Cognitive efficiency(More automatic & effortless)

Grw

Gs (Gv)

Gs (Gq)

Gs (Gc)

Gs (Grw)

Gs(Cognitive speed)


.41

.52.58

.67

.64.52.60.58

.89.76.91 .851.0.83 .82

.86.99.93

.361.0

Alternative Model 2

Close inspection of the evidence suggests that generic dual-system theory is currently oversimplified and misleading

We might be better off talking about type 1 and type 2 processes since all theories seem to contrast fast, automatic, or unconscious processes with those that are slow, effortful, and conscious (Samuels 2006). Such terminology does not commit use to a two-system view. However, it would then be helpful to have some clear basis for this distinction

My suggestion is that type 2 processes are those that require access to a single, capacity-limited central working memory, while type 1 processes do not require such access. This implies that the core features of type 2 processes are that they are slow, sequential, and capacity limited. The last feature implies also that their functioning will correlate with individual differences in cognitive capacity and be disrupted by concurrent working memory load. Depending upon what else is assumed about working memory, there may be a rationale for describing such type 2 processes as registering in consciousness and having properties associated with executive processes and intentional, higher-order control.

GcGq Ga GsmGlr GvGf

g





Type II cognitive processing:More cognitively controlled & deliberate

Type I cognitive processing(Cognitive efficiency):

More automatic & effortless

Grw

Gs (Gv)

Gs (Gq)

Gs (Gc)

Gs (Grw)

Gs(Cognitive speed)

.89.76.91 .851.0.83 .82

.361.0

.64.50.60.58

.41

.52.58

.67

.93 .99

1.0 .86


Alternative Model 2b

GcGq Gv GsmGlr GaGf

g

Grw

Gs (Gv)

Gs (Gq)

Gs (Gc)

Gs (Grw)

Gs(Cognitive speed)

Auditory temporal

(serial) Proc.

Visual/figural (parallel?) Proc.

Cog. knowledge domains/systems

.63.45.60.54

.48.65

.64.73

.89.77.91 .851.0.82 .86 .90

.95.99.94 .21


Alternative Model 3

GcGq Gv GsmGlr GaGf

g

Grw

Gs (Gv)

Gs (Gq)

Gs (Gc)

Gs (Grw)

Gs(Cognitive speed)

Auditory temporal

(serial) Proc.

Visual/figural (parallel?) Proc.

Cog. knowledge domains/systems

Cognitive operations(process/operations/analytic/rule-based

abilities)

.63.45.60.54

.48.66

.64.74

.89.77.91 .851.0.82 .86 .90

.951.0

1.0.94 .21



Pushing the edge of the envelope of CHC theory and the WJ III measurement model: Part II

The first-order measurement model and implications for interpretation of WJ III tests

MEMNAMZ <--- Glr 0.65

STRYRECZ <--- Glr 0.39

VALZ <--- Glr 0.79

DRNAMZ <--- Glr 0.60

DRVALZ <--- Glr 0.73

DRSTRYZ <--- Glr 0.53

MEMSENZ <--- Gsm 0.38

MEMWRDZ <--- Gsm 0.65

AWKMEMZ <--- Gsm 0.74

NUMREVZ <--- Gsm 0.58

Glr and Gsm measurement models were similar tothose originally reported by McGrew & Woodcock (2001)

Calculation 0.14Numbers Reversed 0.19Math Fluency 0.87

Visual MatchingVisual Matching

0.370.54

Cross Out 0.69Pair Cancellation 0.70

Decision SpeedDecision Speed

0.590.18

Retrieval Fluency 0.72

Rapid Picture Naming 0.63Writing Fluency 0.77Reading Fluency 0.82

Gs(Grw)

Gs(Gc)

Gs(Gv)

Gs(Gq)

GGs(Cog Spd)

.62

.64

.55

.59

Gq

Gv

Gc

Grw

.36

.62

.49

.54

Alternative Models: WJ III Measurement model for speed factors

See next slide for otherindicators

See next slide for other

indicators

Vis. Clos. (.41)Blk. Rot. (.52)Spat. Rel. (.66)Pic. Rec (.43)Planning (.43)

Wrd. Atk. (.78) Edit. (.78)Psg. Cmp.* (.55) Wrt. Smp, (.76)Rdg. Voc.* (.34) Spelling (.86)LWrdID (.89)

* Dual loading on Gc on next slide

Gf *

Gf (RQ)

Alternative Models: WJ III Measurement model for possible new

Gf factor structure

Applied Problems 0.26

Quantitative Concepts 0.65

Analysis-Synthesis 0.72Numerical Reas. (Num Series/Matrices) 0.82Concept FormationConcept Formation

0.430.33

Verbal Comprehension 0.23

Sound Awareness 0.79

Understanding Directions 0.74

Gf

Gc

Gq

Gen. Info .(.89)Acd. Knw. (.89)Orl. Cmp. (.77)Psg. Cmp. (.30) (.55-Grw)Rdg. Voc. (.54) (.34-Grw)Mem. Sen. (.36) (.38- Gsm)Story Rec. (.29) (.39-Glr)

Calculation (.75)

Sound Awareness and Understanding Directions did not load on any other factors

Gf * = complex language-based working memory and reasoning?

.99

.34

.27.51

.66

.70

.17

Iteration 1:CHC-basedIntelligence model of WJ

III battery


See handouts for clear

copy

Gf *

Gf (RQ)

Gf

.99

.66

Hmmmm…???

It is time to look at some non-CHC/Gf-Gc research on reasoning (Gf): Alternative lenses

The distinction between inductive and deductive reasoning (i.e., CHC/Gf-Gc Carroll-type model) may be outdated

(Wilhelm, 2005)

Most established reasoning tests confound the direction of inference with deductive and inductive reasoning task

(Whilhelm, 2005)

Whilhelm tested Gf model’s as per CHC (I, RQ, RG) and BIS (verbal, quant, figural) structures, and various model

interactions. The following was the best fitting model

CONFRMOR

ANLSYNER

ANLSYNOR

NUMMATER

ConFrm(I)

AnlSyn(RG)

NumSer(RQ)

NumMat(RQ)

r6

r3

r0

r1

CONFRMERr2

NUMSERER

r7 NUMMATOR

NUMSEROR

r4

r5

.94

.94

.94

.95

.95

.94

.94

.95

.79

.72

. 76

.72

. 68

.81

CFA using dual indicators (split-half—odd/even item sets) for each test:

Conclusion: WJ III RG, I, RQ tests are highly correlated but do measure different aspects of Gf

CONFRMOR

ANLSYNER

ANLSYNOR

NUMMATER

ConFrm(I)

AnlSyn(RG)

NumSer(RQ)

NumMat(RQ)

r6

r3

r0

r1

CONFRMERr2

NUMSERER

r7 NUMMATOR

NUMSEROR

r4

r5

.94

.94

.94

.95

.95

.94

.94

.95

RQ

f3

f4

f2

f1

f5

.93

.88

Gf

.91

.86

.90

WJ III CHC Gf model

Fit for this and prior model (prior slide) more-or-less equivalent

CONFRMOR

ANLSYNER

ANLSYNOR

NUMMATER

ConFrm

AnlSyn

NumSer

NumMat

r6

r3

r0

r1

CONFRMERr2f2

f3

f4

NUMSERER

r7 NUMMATOR

NUMSEROR

r4

r5

f1

.94

.94

.94

.95

.95

.94

Gq

.94

.95

Gf

f7

APPROBER

APPROBOR

CALCER

r8

r9

r10

AppPrb

CALCORr11 Calc

f5

f6

.88

.90

.88

.87

.65

ORLVOCER

PICVOCER

PICVOCOR

GENINFOR

GENINFER

ACKNOWOR

ACKNOWER

ORLVOCOR

VERBANLER

VERBANLOR

.93

PicVoc

GenInf

AcdKnw

OrlVoc

VrbAnl

r12

r13

r14

r15

r16

r17

r18

r19

r20

r21

.82

.74

.96

.95

.90

.91

.91

.92

.85

.90

Gc

f8

f9

f10

f11

f12

.94

.97

.98

.77.21

Gf(lang)

f13

.21

.73

.99

SNDAWRER

SNDAWROR

r22

UNDDIRER

UNDDIROR

r23

r24

r25

SndAwr

UndDir

f14

f15

.89

.96

.96

.96

.96

Gf(vis)

f16

.58

.92

.92

Gf(qnt)

.35

.87

.94

.33

f17

g

.88

.99

.89

.93

f18

f19

.97

Gf sub-abilities differentiated by content/stimulus features (Wilhelm model)

Although some fit stats are slightly better for this model (when compared tomodel on prior slide) using practical criteria they are more-or-less equivalent

Important Reminder: All statistical methods, suchas factor analysis (EFA or CFA) have limitations and constraints.

It only provides evidence of structural/internal validity and typically nothing about external, developmental, heritability, neurocognitive validity evidence

Need to examine other sources of evidence and use other methods – looking/thinking outside the factor analysis box

-3 -1 1 3

Language (verbal/aud.)--------Nonverbal (#’s,visual)

-3

-1

1

3

PicVoc GenInf

OrlVoc

AcdKn

VrbAnlAnlSyn

NumMat

Calc

ConFrm

NumSer

ApPrb

UndDir

SndAwr

Re

as

on

ing

(p

roc

ed

ura

l/G

f)--

----

-Re

ca

ll (

de

cla

rati

ve

/Gc

/Gq

))

Lang (aud-verbal)

#/quant.

Visual-figural

Guttman Radex MDS model of WJ III Gf, Gc, and Gq test indicators

Additional support for differentiation of Gf by type of content or stimulus features

Note which tests are near the center: More cognitively complex

• Snd Awareness• Under.

Directions.

"If one writes a book on neuropsychological assessment, thou shall not write a book that is less than 3 inches thick or less than 3

lbs in weight“ (McGrew, August 13, 2010)

The First Commandment of Neuropsychological Assessment

Lets look at the pieces one by one –

blow them up

Strauss et al. (2006)

Lezak et al. (2004)

Rabin et al. (2005)

Shaughnessy& O'Connor

(2009)

Miller (2010)

Flanaganet al. (2010)

Gen int./ cognition

(CHC model)

Concept formation &

reasoning

(verbal; visual; arith. reas.)

Intelligence

Intellectual

Gen intelligence(CHC model)

Gen intelligence

(CHC model)

Language

Verbal functions/Language Language

Language

Language

Language

Achievement

Math proced. (CF & reason)

(Calculations)

Verbal functions (Verbal

Acd. Skills)

Achievement

Language (Rdg & Wrtg)

Academic achievement

Memory & Learning

(ach domains)

Arm-chair factor analysis of neuropsych. assessment domains [and CHC construct mapping] (K. McGrew; 8-18-10) [I of 3]

gGf

Gc

GrwGq


Lezak et al. (2004)

Rabin et al. (2005)

Shaughnessy& O'Connor (2009)

Miller (2010)


Visual-spatial

Perception (Visual)

Construction

Visual spatial skills

Construction

Visuoperceptual/Visuospatial/

Visuoconstruction

Visual-spatial

Visual-spatial

Perception (Auditory)

Auditory Perception

Language (analysis of

sounds)Language

(phonological processing)

Auditory-Verbal

Memory

Memory

Verbal Memory

Nonverbal Memory

Memory

Memory & learning

Memory & learning

Gv

GsmGlr

Ga



Lezak et al. (2004)

Rabin et al. (2005)

Shaughnessy& O'Connor (2009)

Miller (2010)


Speed & efficiency *

Speed & efficiency

Attention

Executive functions

Orientation & attention

Executive functions

& motor perf.

Attention

Executive functions

Attention

Frontal executive functions

Attentional

Executive functions

Attention

Executive

Somatosensory/olfactory; body

orientation

Motor function

Perception (tactile;

olfaction)

Exec func (motor perf.)

Tactile Perception

Motor Skills

Sensory & motor

Sensorimotor

Sensory-motor

GsGsm

GpGpsGoGhGk

AC??


Hypothesized (“working”) CHC-based intelligence model (iteration 2)

Kevin McGrew (8-26-2010)

Mapping of current CHC domains with hypothesized

new CHC-based

intelligence model


Lets look at the pieces one by one – blow

them up

Cognitive Content/Stimulus Dimensions

Cog. KnowledgeDomains/Systems

Language Numerical - Visual- Somata- Olfactory

(aud-verb) Quantitative Figural sensory General Acquired Knowledge Gc, Grw Gq ? Gh/Gk Go

Domain-specific Knowledge Gkn Gkn Gkn Gkn Gkn

Empirical examples of Gkn domainsFrom Carroll (1993)

Empirical examples of Gkn

domains

Ackerman et al. research group


Cognitive Operations Language(aud-verb)

Numerical -Quantitative

Visual- Figural

Somata-sensory

Olfactory

Complex Reasoning Gf (lang.)

Gf (quant.)

Gf

(Vis-figural)

? ?

Long-term storage & retrieval Glr ( ) Glr ( ) Glr ( ) ? ?

Processing (perceptual) Ga ? Gv Gh/Gk Go


Cognitive EfficiencyLanguage(auditory-

verbal)


Visual- Figural

Somata-sensory

Olfactory

Short-term/Working Memory

Gsm ( ) Gsm ( ) Gsm ( ) ? ?

Processing Speed Gs(Gc)Gs(Grw)

Gs(Gq) Gs(Gv)? ?

Cognitive Control

Executive Functions

Controlled Executive Attention

Cognitive Content/Stimulus DimensionsSensory Language

(auditory-verbal)


Visual- Figural

Somata-Sensory

Olfactory

Vision

Hearing

Tactile

Gh

Kinesthetic Gk

Olfactory Go

Motor

Psychomotor Abilities

Psychomotor Speed Gp and Gps across domains

.

The cortical homunculus was discovered by Wilder Penfield

The somatosensory system

http://en.wikipedia.org/wiki/File:Sensory_Homunculus.png

http://en.wikipedia.org/wiki/Cortical_homunculus

http://en.wikipedia.org/wiki/Wilder_Penfield

http://en.wikipedia.org/wiki/File:Sensory_Homunculus.png

Olfactory abilities/functioning (Go)

Olfactory abilities/functioning (Go): Possiblesub-abilities mentioned in the literature

• Olfactory memory (OM)• Odor-evoked memories• Episodic odor memory• Olfactory store in working memory

• Olfactory sensitivity (OS) /detection• Odor specific abilities (O1, O2, O3, O4)• Odor identification/recognition/detection /discrimination• Olfactory thresholds (and reaction time)• Olfactory acuity• Semantic odor networks/odor naming• Olfactory imagery• Odor discrimination• Odor awareness• Sexual role of odors• Ecological odor sensitivity

Olfactory abilities/functioning (Go): Dx importance(Doty, 2001)

This is research/work in progress: Suggested research that needs to be explored and integrated. Go from here

to……………..




g loading






Metric scale




Somata

senso

ry

Langu

age (a

ud.-verb

.)

Olfacto

ry

Visual-

figural

Numerical/

quant.

Content/stimulus dimension

Low

High

Cognitv

e complexit

y

dimensio

n

This is NOT a model of human functioning – it is a “working” heuristic of Kevin McGrew’s current hypothesized thinking (iteration 3?) regarding the important dimensions that may

be important in the development and interpretation of measures of human abilities …………. (not a Guilford SOI model where all cells are believed to exist)

Cognitive knowledge domains/systems

Cognitive operations

Cognitive control

Cognitive efficiency

Sensory functions

Motor functions

Abilt

y do

mai

n di

men

sion

Type

IPr

oces

sing

Type

IIPr

oces

sing

Note: CHC taxonomy is embedded in the ability domain dimension (see prior slides)

?: Is the low-how cog. complexity continuum simply a continuous

representation of the Type 1/I processing distinction ?

g – speed ?

• Numerical Fluency (N)• Speed of Reasoning (RE) **• Reading Speed (RS) ***

• Pattern Recognition (Ppr)• Scanning (Ps)• Memory (Pm)• Complex (Pc)

PPerceptual

Speed *

• Simple Reaction Time (R1)• Choice Reaction Time (R2)• Semantic Processing Speed (R4)• Mental Comparison Speed (R7)

Stratum III(General)

Stratum II(Broad)

Stratum I(Narrow)

Figure 2: Hypothesized speed hierarchy based on integration of Carroll (1993) speed abilities with recent research (Ackerman, Beier & Boyle, 2002; O’Connor & Burns, 2003; McGrew & Woodcock, 2001; Roberts & Stankov, 1998; Stankov, 2000; Stankov & Roberts, 1997)

• Speed of Limb Movement (R3)• Wrist-finger Speed (P5)• Speed of Articulation (PT)• Speed of Writing (WS) ****

GpBroad Psycho-Motor Ability

• Static Strength (P3)• Multilimb Coordination

(P6)• Finger Dexterity (P2)• Manual Dexterity (P1)• Arm-hand Steadiness (P7)• Control Precision (P8)• Aiming (AI)

RTReaction

Time

MTMovement

Time

* Carroll classified P and R9 as narrow abilities under Gs/Gv and Gt, respectively ** Classified as speed and level (Gf) ability by Carroll *** Classified as a speed and level (Gc) ability by Carroll Also classified under Grw by the current author **** Classified as Psychomotor Ability by Carroll. Also classified under Grw by current author

[ Narrow P abilities suggested by Ackerman et al. (2002) ]

GtBroad Decision

Speed

GsBroad Cognitive

Speed

R9Rate-of-test

Taking *

GpsBroad Psycho-Motor Speed

Integrate proposed g-speed hierarchy (McGrew & Evans, 2004; McGrew, 2005)

GcGq Ga GsmGlr GvGf

g





Type II cognitive processing:More cognitively controlled & deliberate

Type I cognitive processing(Cognitive efficiency):

More automatic & effortless

Grw

Gs (Gv)

Gs (Gq)

Gs (Gc)

Gs (Grw)

Gs(Cognitive speed)

.89.76.91 .851.0.83 .82

.361.0

.64.50.60.58

.41

.52.58

.67

.93 .99

1.0 .86



g – speed ?

CONFRMOR

ANLSYNER

ANLSYNOR

NUMMATER

ConFrm

AnlSyn

NumSer

NumMat

r6

r3

r0

r1

CONFRMERr2f2

f3

f4

NUMSERER

r7 NUMMATOR

NUMSEROR

r4

r5

f1

.94

.94

.94

.95

.95

.94

Gq

.94

.95

Gf

f7

APPROBER

APPROBOR

CALCER

r8

r9

r10

AppPrb

CALCORr11 Calc

f5

f6

.88

.90

.88

.87

.65

ORLVOCER

PICVOCER

PICVOCOR

GENINFOR

GENINFER

ACKNOWOR

ACKNOWER

ORLVOCOR

VERBANLER

VERBANLOR

.93

PicVoc

GenInf

AcdKnw

OrlVoc

VrbAnl

r12

r13

r14

r15

r16

r17

r18

r19

r20

r21

.82

.74

.96

.95

.90

.91

.91

.92

.85

.90

Gc

f8

f9

f10

f11

f12

.94

.97

.98

.77.21

Gf(lang)

f13

.21

.73

.99

SNDAWRER

SNDAWROR

r22

UNDDIRER

UNDDIROR

r23

r24

r25

SndAwr

UndDir

f14

f15

.89

.96

.96

.96

.96

Gf(vis)

f16

.58

.92

.92

Gf(qnt)

.35

.87

.94

.33

f17

g

.88

.99

.89

.93

f18

f19

.97

Gf sub-abilities differentiated by content/stimulus features (Wilhelm model)

Additional dual-indicator modeling of WJ III data in other domains (e.g., Gsm,

Glr, Ga, Gv, Gq, Grw)

Reconcile and integrate Johnson & Bouchard VPR (Verbal-Perceptual-Image Rotation) psychometric model of intelligence with working CHC model

Integrate and conceptualize working model within

information processing models

Figure 4: WJ III CHC information processing g causal model (ages 14-19)

Gf

Gv

Gs

Glr

Ga

Gc

.69

.47

.53

.78

.66

.81

.50

.69

.72

.74

.58

.40

g

.83

.95

.87

.77

.92

.49

.74

.94

.59

.88

.74

.78

.78

.78

.75

.72

.72

.80.27

.07

.82

.07

MS

MW

Memory for Names

Picture Recognition

Vis-Aud Lrng (VAL)

Del Recall-VAL

Retrieval Fluency

Numerical Reas

Concept Formation

Analysis-Synthesis

General Information

Oral Comp

Verbal Comp

Sound Blending

Sound Patterns

Incomplete Words

Block Rotation

Spatial Relations

Visual Matching

Decision Speed

Cross Out

Mem for Sentences

Mem for Words

Aud Working Mem

Numbers Reversed

76 % of g variance explained

Note: Ovals representlatent factors. Rectangles represent manifest measures (tests). Single-headed arrows to tests from ovals designate factor loadings. Single headed arrows between ovals represent causal paths (effects). Test and factor residuals omitted for readability purposes.

Cognitive Efficiency

And…..the state-of-the art research being conducted on working memory

I particularly favor the models and research of:

Conway, Engle and Kane group– Human working memory lab – Princeton, NJ.

• Controlled executive attention model

Torkel Klingberg group - Karolinska Institute-Stockholm Brain Institute

Integrate and conceptualize working model

within dual-processing neuro-cognitive research

and models

Integrate working model with Haier and colleagues parieto-frontal integration theory (P-FIT)

P-FIT model

P-FIT model researchers are mapping brain areas to CHC domain constructs

Gc

Gv

Timescales of temporal processing

(Mauk & Buonomano, 2004)

Humans processtemporal information over scales of at least 10-12 orders of magnitude that have been categorized into 3-4 major timescale groups

Mental Timing Research:Has been implicated as important in human learning

and understanding a variety of clinical disorders. Examples include:

• Parkinson’s

• Huntington’s

• Schizophrenia

• ADHD

• Reading development and disorders (dyslexia/reading disabilities)

• Speech and language development and related disorders• Analogy – auditory processing of Morse code

• Musical abilities and performance

• Motor timing disorders

• Aspergers???

(See IQ BrainClock EWOKfor research)

Research suggests common dopamine link (e.g., dopaminergic disorders)

Temporal information processing models (Creelman, 1962; Gibbon, 1991; Rammsayer & Ulrich, 2001; Treisman et al., 1990; see Grondin, 2001 for review) are based on the central assumption of neural oscilliations (note – same central feature of Jensen’s neural efficiency theory of g) as a major determinant of timing performance.

The higher the frequency (higher speed) of neural oscillations the finer the temporal resolution of the internal clock = greater timing accuracy (Rammsayer & Brandler; 2007)

Integrate working model with temporal g (brain clock) research

Analyses suggested a unitary timing mechanism, referred to as temporal g.

Performance on temporal information processing provided a more valid predictor of psychometric g than traditional reaction time measures

r (with psychometric g) = .56 (temporal g) vs .34 (reaction time g)

Findings suggest that temporal resolution capacity of the brain (as assessed with psychophysical temporal tasks) reflects aspects of neural efficiency associated with general intelligence.

Rammsayer & Brandler (2007)

Temporal g ?

Automatic timing system

• Works in the millisecond range• Discrete-event (discontinuous) timing,

esp. movement/motor tasks• Involves the cerebellum

Cognitively-controlled timing system

• Continuous-event timing• Requires attention and involvement of

working memory• Involves the basal ganglia and related

cortical structures

It is the “constellation of task characteristics that dictate which timing “circuits” of brain “systems”are invoked in a particular task performance (Lewis & Miall, 2006)

Two primary mental timing circuits

(Buhusi & Meck, 2005; Lewis & Miall, 2006)

In conclusion.....




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