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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
“ 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
PMA2 PMA3 PMA4 …etc
…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
PMA2 PMA3 PMA4 …etc
…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
PMA2 PMA3 PMA4 …etc
…etc
G1 G2 G3…etc
g ?
(1e) Consensus Cattell-Horn-Carroll Hierarchical Three-Stratum Model
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
PMA2 PMA3 PMA4 …etc
…etc
G1 G2 G3
…etc
g ?
(1e) Consensus Cattell-Horn-Carroll Hierarchical Three-Stratum Model
CHC as the consensus psychometric model of
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
PMA2 PMA3 PMA4 …etc
…etc
G1 G2 G3
…etc
g ?
(1e) Consensus Cattell-Horn-Carroll Hierarchical Three-Stratum Model
CHC as the consensus psychometric model of
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)
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)
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
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)
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+
MVGv
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
© Institute for Applied Psychometrics llc 8-24-03
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)
© Institute for Applied Psychometrics, llc 02-05-02
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
r8
r10
r11
r12
r13
r14
r15
r16
r17
r18
r19
r20
r21
r40
r41
r39
r38
r37
r36
r35
r34
r33
r32
r31
r30
r29
r28
r27
r26
r25
r24
r23
r22
r9
r42r43
r44
Gc
Gsm
GrwGf
Gv
Gs
Ga
Glr
f2
f1
f9
f7
f6
f3
f5
f8
g
.70
.70
.89
.66
.71Gq
f10
.72
r5
.38
.45
.69
.22
.90
.80
.19.24
.50
.73
.26
.57
.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
.32
.64
.52.47
.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)
© Institute for Applied Psychometrics, llc 02-05-02
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
r8
r10
r11
r12
r13
r14
r15
r16
r17
r18
r19
r20
r21
r40
r41
r39
r38
r37
r36
r35
r34
r33
r32
r31
r30
r29
r28
r27
r26
r25
r24
r23
r22
r9
r42r43
r44
Gc
Gsm
GrwGf
Gv
Gs
Ga
Glr
f2
f1
f9
f7
f6
f3
f5
f8
g
.70
.70
.89
.66
.71Gq
f10
.72
r5
.38
.45
.69
.22
.90
.80
.19.24
.50
.73
.26
.57
.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
.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
© Institute for Applied Psychometrics llc 12-07-03
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
“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
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)
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
.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
Cog. knowledge domains/systems(product/content abilities)
Lang/linguistic./symbolic abilities
Cognitive operations(process/operations/analytic/rule-
based abilities) figural-spatial, lower-linguistic abilities
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
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 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
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 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
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 3b
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
Kevin McGrew8-18-2010
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
Strauss et al. (2006)
Lezak et al. (2004)
Rabin et al. (2005)
Shaughnessy& O'Connor (2009)
Miller (2010)
Flanaganet al. (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
Arm-chair factor analysis of neuropsych. assessment domains [and CHC construct mapping] (K. McGrew; 8-18-10) [I of 3]
Strauss et al. (2006)
Lezak et al. (2004)
Rabin et al. (2005)
Shaughnessy& O'Connor (2009)
Miller (2010)
Flanaganet al. (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??
Arm-chair factor analysis of neuropsych. assessment domains [and CHC construct mapping] (K. McGrew; 8-18-10) [I of 3]
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
Kevin McGrew8-18-2010
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 Content/Stimulus Dimensions
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 Content/Stimulus Dimensions
Cognitive EfficiencyLanguage(auditory-
verbal)
Numerical -Quantitative
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)
Numerical -Quantitative
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
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……………..
“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
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
Cog. knowledge domains/systems(product/content abilities)
Lang/linguistic./symbolic abilities
Cognitive operations(process/operations/analytic/rule-
based abilities) figural-spatial, lower-linguistic abilities
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
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 2b
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.....
“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