WJ IV NASP 2014 workshop: Cognitive and Oral Language batteries by Dr. Kevin McGrew

WJ IV Tests of Cognitive Ability: Overview of
GIA and CHC factor clusters, new and revised
tests, and select data analysis results
Dr. Kevin McGrew
Institute for Applied Psychometrics (IAP)

© Institute for Applied Psychometrics; Kevin
McGrew 2-04-14

Kevin McGrew WJ IV
Presentation Outline
• Overview of WJ IV COG/OL system
• New or repurposed COG tests
• Technical tidbits (through out)
• The COG battery design principles
• Featuring cognitive complexity

• WJ IV COG tests and clusters with a dash of data
© Institute for Applied Psychometrics; Kevin McGrew 01-23-14

Note: technical
information was
included in
sides during live
presentation
but have been
removed since
they are not yet
officially
published in
technical
manual

Gf

Gc

Gwm

Gs

Ga

Glr

Gv

General Intellectual Ability – g (7)
Brief Intellectual Ability (3)

Gf+Gc Composite (4)
Fld. Reas.
(2)

Cmp. Know.
(2)

ST Wk. Mem.
(2)

Clusters available from
Standard Cognitive
easel
(10 tests)
(#) = # tests

Cognitive Efficiency (2)
Fld. Reas.
(3)

Cmp. Know.
(3)

ST Wk.
Mem. (3)

Qnt. Reas.
(2)

Cog. Pr. Spd.
(2)

Aud. Proc.
(2)

LT Retrieval
(2)

Visual. Proc.
(2)

Perc. Spd.
(2)
Number Facility (2)

Other clusters
available by
combining Standard
Cognitive tests with
select tests from
Extended Cognitive
easel (8 tests)

Cognitive Efficiency (4)
Reading, Math and Writing Scholastic Aptitudes (each comprised of a mix of 4 different CHC abilities)

Vocab.
(2)

Aud. Mm. Sp.
(2)

(These two clusters require one test each from
Cognitive and Oral Language easels)

Broad Oral Lang (3)*

Phon. Cod.
(2)

Spd. Lx. Acc.
(2)

Oral Lang.
(2)*
Oral Expression (2)
Listening Comp. (2)*

(#) = # tests

(* English or Spanish)

Organization of WJ IV Cognitive (COG) and Oral Language (OL) batteries

Clusters available
from Oral Language
easel(12 tests)
(#) = # tests

Gf

Gc

Gwm

Gs

Ga

Glr

Gv

General Intellectual Ability – g (7)
Brief Intellectual Ability (3)

Clusters available from
Standard Cognitive easel
(10 tests)

Gf+Gc
Composite (4)
Fld. Reas.
(2)

Cmp.
Knw.(2)

(#) = # tests

ST Work.
Mem. (2)

Cognitive
Efficiency (2)
Fld. Reas.
(3)

Qnt. Reas.
(3)

Cmp.
Knw.(3)

ST Work.
Mem. (3)

Cog. Proc.
Speed(2)
Perc.
Speed(2)

Number
Facility (2)

Aud. Proc.
(2)

LT Ret.
(2)

Visual
Proc. (2)

Other clusters available by
combining Standard Cognitive
tests with select tests from
Extended Cognitive easel (8 tests)

Cognitive
Efficiency (4)
Scholastic Aptitude Clusters (each a mix of 4 CHC abilities)

Contemporary CHC broad and narrow ability content
coverage by WJ IV Cognitive (as per WJ IV authors)
General
Intelligence (g)
DomainSpecific Knw.
(Gkn)

Quantitative
Knowledge
(Gq)

Reading &
Writing (Grw)

Comp Knowledge
(Gc)

Fluid
Reasoning (Gf)

General science
info. (K1)

Mathematical
achievement
(A3)

Reading
decoding (RD)

Language
development
(LD)

Induction (I)

Knowledge of
culture (K2)

Reading
comprehension
(RC)

General verbal
information (K0)

Geography ach.
(A5)

Verbal (print)
lang. comp. (V)

Lexical
knowledge (VL)

Reading speed
(RS)

Short-Term

Listening ability
(LS)

Spelling ability
(SG)

Long-Term
Retrieval (Glr)

Visual
Processing (Gv)

Auditory
Processing
(Ga)

Speed (Gs)

Memory span
(MS)

Associative
memory (MA)

Visualization
(Vz)

Phonetic coding
(PC)

Perceptual speed
(P)

General
sequential
reasoning (RG)

Working memory
capacity (WM)

Meaningful
memory (MM)

Visual Memory
(MV)

Memory for
Sound Patterns
(UM)

Number Facility
(N)

Quantitative
reasoning (RQ)

Attentional
Control (AC)

Naming facility
(NA)

Spatial Scanning
(SS)

Work Mem
(Gwm)

Speed of Lexical
access (LA)

NEW

Word Fluency
(FW)

English usage
(EU)

Writing ability
(WA)

Shading designates abilities
measured by WJ IV COG battery

Writing speed
(WS)


Processing

WJ IV COG and OL tests by CHC
factor domains
CHC Factors
Gc

Gf

Gwm

Glr

Gv

Ga

Gs

Story Recall

Visualization

(MM)

(Vz)

Phonological
Processing

Letter-Pat.
Matching

(PC/Glr-LA)

(P)

Nonword
Repetition

Pair
Cancellation

(PC/UM-MS)

(P/WM-AC)

Oral
Vocabulary

Number
Series

Verbal
Attention

(VL)

(RQ)

(WM/AC)

General
Information

Concept
Formation

Numbers
Reversed

Visual-Aud.
Learning

Picture
Recognition

(K0)

(I)

(WM)

(MA)

(MV)

Picture
Vocabulary

AnalysisSynthesis

Memory for
Words

Rapid Picture
Naming

(VL/LD)

(RG)

(MS)

(NA/LA)

Object-Num.
Sequencing

Retrieval
Fluency

Sound
Blending

(WM)

(FI/LA)

(PC)

Oral Comp.
(LS)

Segmentation
(PC)

Sentence
Repetition

Sound
Awareness

(MS)

(PC)

Under.
Directions
(WM/Gc-LS)

COG
OL


New or sign.
change

Number-Pat.
Matching
(P)

Two primary WJ IV COG design decisions
Gc

Gf

Gwm

Oral
Vocabulary

Number
Series

Verbal
Attention

General
Information

Concept
Formation

Numbers
Reversed

AnalysisSynthesis

Memory for
Words

Glr

Gv

Story Recall

Visualization

Visual-Aud
Learning

Picture
Recognition

Ga

Phon.

Gs

Processing

Letter-Pat.
Match.

Nonword

Pair

Repetition

Cancellation
Number-Pat
Match.

Obj-Num.
Sequencing

• Which 7 tests should be combined for the GIA (g) cluster?
• Which 2 tests from each CHC factor domain should be
combined for the 7 CHC factor clusters?

Comparison of composition of primary
WJ III and WJ IV COG CHC and GIA clusters
Gc

Gf

Gwm

Glr

Gv

Ga

g

Gs

Primary WJ III and WJ IV COG tests and Clusters
Verbal

Oral
Vocabulary

Number
Series

Attention

General
Information

Concept
Formation

Numbers
Reversed

Verbal
Comp.

AnalysisSynthesis

Memory for
Words

Story Recall Visualization

Picture
Visual-Aud
Learning Recognition

Phon.
Processing

Letter-Pat.
Match.

Nonword

Pair

Repetition

Canc.

Retrieval

Spatial

Sound

Visual

Fluency

Relations

Blending

Matching *

Auditory
Attention

GIA

Decision

(WJ IV Oral Vocab. was
part
of WJ III Verbal Comp.)

(WJ III Spatial
Relations is half of
WJ IV Visualization)

Tests in WJ IV
COG clusters

WJ IV GIA

Tests in WJ III
COG Clusters

GIA Standard

Speed

WJ III GIA-Standard

* Visual Matching is renamed Number-Pattern
Matching in WJ IV
McGrew 01-23-14

The WJ IV COG is not your fathers intelligence test!
The WJ IV COG GIA is a much more cognitively
complex (and high g) measure of intelligence
How did we do this?
What evidence do we have to support this conclusion?

WJ IV Tests of Cognitive Ability: Overview
and select data analysis results
How do the general intelligence (g)
clusters scores from ………….

Compare to the general intelligence
(g) total scores from …………


Select concurrent validity evidence:
Correlations of WJ IV primary COG g-scores
with external measures
WISC-IV WAIS-IV WPPSI-III KABC-II
FS IQ
FS IQ
FS IQ
FCI
(n =174) (n =177) (n = 99)

(n=50)

SB-5
FS IQ

DAS-II
GCA

(n = 50)

(n = 49)

WJ IV g-measures
(see prior note regarding technical info presented at NASP that can’t be released
yet until tech. manual published)

Conclusion: The WJ IV GIA, BIA and Gf-Gc composite clusters
demonstrate strong validity evidence as measures of general
intelligence when the criterion are the global composite/total
scores from other major IQ batteries in the field

Yet to be published preliminary cross-battery gloading and cognitive complexity analysis of
primary WJ IV/external IQ battery special studies
Spatial position
from center of MDS
Guttman radex
analysis “maps”
g-loadings based on
factor/principal
component analysis

g

T1

T2

T3

T4

T5

T6

T7

T8

T9 T10 T11 T12

(1a) Spearman’s general Factor model

© Institute for Applied Psychometrics;
Kevin McGrew 01-23-14

1-factor (unrotated) common-factor solution for WJ IV
COG / WISC-IV composite scores (n=173)

Verbal Comprehension Index (VCI)
Auditory Processing (Ga)
Fluid Reasoning (Gf)
Perceptual Reasoning Index (PR)
Comprehension-Knowledge (Gc)
Short-Term Work. Memory (Gwm)
Working Memory Index (WMI)
Long-Term Retrieval (Glr)
Visual Processing (Gv)
Processing Speed Index (PSI)
Cog. Processing Speed (Gs)



Loadings on Communality
first unrotated
Estimates
common factor
0.809
0.654
0.804
0.646
0.804
0.646
0.800
0.639
0.779
0.607
0.764
0.584
0.749
0.562
0.683
0.466
0.604
0.365
0.569
0.323
0.537
0.288

•The WJ IV GIA score is as
good (better?) a measure of
general intelligence (g) as
the WISC-IV FS IQ when
defined by g-loadings and
MDS cognitive complexity
analysis.

Measures closer to the center of
the radex of more cognitively
complex

2

1

GWM

GV

WMI

PRI

FSIQ

PSI



0

• The WJ IV Ga cluster is a
measure of complex
cognitive abilities;
comparable to WJ IV &
WISC-IV Gf/PRI composites.

GF VCI
GIA

GA



GLR

-1

GC

GS

-2
-2

-1

0

1

2 MDS solution for WJ IV / WISC-IV
composite and g-scores (n=173)

2

•The WJ IV measures
cognitive abilities not
represented in the WISC-IV
(Ga, Glr, and possibly Gv).

The WJ IV Auditory Processing (Ga) cluster
is not your fathers Ga measure.
WJ IV still has the Oldsmobile Ga
(Phonetic Coding) in OL: COG now has
more cognitively complex Ga measures

The WJ IV has taken a broader
contemporary view of the domain of Ga

Auditory Processing (Ga) abilities
should no longer be considered the
Rodney Dangerfield of CHC abilities
School psych. and SLD have had a myopic “lamp
post-search ” blinder focus on only one part of the
very broad domain of Ga
There has been an explosion of research (since
Carroll’s 1993 treatise) that has identified potentially
new important and cognitively complex Ga narrow
abilities

Auditory Processing (Ga) abilities, when
properly measured, should have a
prominent chair at the roundtable of
cognitive CHC abilities


Five primary design principles for WJ IV COG GIA
The WJ IV COG GIA cluster tests should:
1. Be the best factor indicators of each CHC broad domain
2. Be the best predictors of achievement from each CHC broad
domain
3. Be the most cognitively complex indicators from each CHC
broad domain

4. Be the best measures of g (general intelligence) from each
CHC broad domain
5. Collectively should have a relatively equal balance of type of
stimulus characteristics (verbal, numeric, figural)

Related

What is cognitive complexity?

CHC factor breadth
Cognitive
complexity

Factorial complexity
(Does not
necessarily
equal)

Degree of g-loading
Complicated


Cognitively complex design characteristics
(Lohman, 2011)
• Larger number of cognitive component processes
Parameters
of cognitive
efficiency
in info.
proc.
models

• Accumulation of speed component differences
• Increased demands of attentional control (AC) &
working memory

• More important component processes (e.g.,
inference)
• More demands on adaptive functions (assembly,
control, and monitoring).

One design objective in the WJ IV was to increase the
cognitive complexity requirements for selected tests
and clusters to provide greater ecological validity and
interpretive relevance of the measures.
Approach 1. Increasing the cognitive complexity of a test is often
accomplished by making the test a mixed measure of more than one narrow
CHC ability (factorially complex mixed CHC measures)
Approach 2. A second approach is to increase the complexity of information
processing demands of the tests within a specific narrow CHC domain
(Lohman & Larkin, 2011; McGrew, in press b). This second form of cognitive
complexity, not to be confused with factorial complexity, places greater
demands on cognitive information processing (cognitive load), requires
greater allocation of key cognitive resources (working memory or attentional
control), and invokes the involvement of more cognitive control or executive
functions (Arend, Colom, Botella, Contreras, Rubio, & Santacreu, 2003;
Jensen, 2011; Lohman & Larkin, 2011; Marshalek, Lohman, & Snow; 1983).
This second approach to increasing test cognitive complexity was a primary
design principle for the WJ IV.

Analogy: Think of general intelligence (g) as a system of
relatively independent cognitive abilities (relatively construct
“pure” pulleys) working together to deal with a specific
cognitive task load
Gf

© Institute for Applied
Psychometrics; Kevin
McGrew 01-23-14

Gwm

Gc

Ga

Gs

Gv

Glr

G?

Most contemporary CHC designed individual tests have focused on
developing relatively pure measures of each cognitive ability
(mental pulley)

Approach 1 to developing cognitively complex tests –
Construct factorially complex measures (a system of
pulleys from 2 or more domain functions working in
combination).
Gf + Gv
Gf +

Gv

Gwm Gc Ga Glr Gv Gs

Psychometrics; Kevin McGrew
01-23-14

In this approach a test is designed to be a mixed measure of
two (or more) cognitive abilities (mental pulleys; Gf + Gv)

Approach 1 example
Gf + Gv

Gf + Gwm + Gc +

Gq

Ga Glr Gv

Gs

Psychometrics; Kevin McGrew
01-23-14

Wechsler Arithmetic test

Approach 2 is to increase the complexity of information
processing demands of the tests within a specific CHC
cognitive functional domain. Tasks are still as relatively pure a
measure of the CHC domain as possible but there is a
deliberate increase in the number of “mini-pulleys” (cognitive
information component complexity) that work together within
the CHC domain. This was the primary approach used for
certain WJ IV tests.
Ga

Gv

Gwm


Gc Gf Glr Gv Gs

Professor Butts and the “over
engineered” self-operating
napkin machine (aka., Rube
Goldberg machines)

COG Test 5: Phonological
Processing
• Ga (PC) / Glr (LA/FW)
•3 subtests (Word Access; Word Fluency; Substitution
• Measures three aspects of speech sound processing
that requires the efficiency construction of soundbased lexical representations
• High in cognitive complexity and g. Best single Ga
test predictor of achievement. High loading on Ga
and secondary low loading on Gc (accessing the
lexicon). Also loaded on narrow LA factor in
broard+narrow bottom-up CFA models.
• In GIA, Ga, and all reading and writing scholastic
aptitude clusters

COG Test 5A: Phonological ProcessingWord Access

• Word Access: Examinee provides a word that has
a specific phonemic element in a specific location

(Sample items deleted for test security reasons)

COG Test 5B: Phonological ProcessingWord Fluency
• Word Fluency: Examinee names as many words as
possible that begin with a specified sound in 1 minute


COG Test 5B: Phonological ProcessingSubstitution
• Substitution: Examinee substitutes part of a word to
create a new word


Five primary design principles for WJ IV COG GIA


1. Be the best factor indicators of each CHC
broad domain
2. Be the best predictors of achievement from each CHC broad domain
3. Be the most cognitively complex indicators from each CHC broad domain
4. Be the best measures of g (general intelligence) from each CHC broad
domain
5. Collectively should have a relatively equal balance of type of stimulus
characteristics (verbal, numeric, figural)
(Note: Trade-offs between the four design objectives were sometimes necessary)


Three-stage internal/ structural validity procedures for WJ IV battery
Stage 1:
Split-sample
random sample
generation
(total n = 7,416)
Model
Development
(MD)
samples (A)
Ages 3-5 A
(n = 209)

Model
Cross-Validation
(MCV)
samples (B)
Ages 3-5 B
(n = 208)

Stage 2:
Exploratory structural model
generation (MG) and evaluation

Stage 3:
Confirmatory
structural
model crossvalidation
phase

Stage 2 a
Exploratory structural
analysis in Sample A

Cluster analysis
(CA)

Model adjustment(s)
No

Ages 6-8 B
(n = 411)

+

Ages 9-13 A
(n = 785)

Ages 9-13 B
(n = 787)

Principal
component
analysis
(PCA)

Ages 14-19 A
(n = 842)

Ages 14-19 B
(n = 843)

Ages 20-39 A
(n = 625)

Ages 20-39 B
(n = 626)

Ages 40-90+ A
(n = 571)

Ages 40-90+ B
(n = 575 )

Ages 6-8 A
(n =412)

Specify initial
confirmatory
factor analysis
model (CFA)

+
Multidimensional
scaling analysis
(MDS)

Review of
contemporary
CHC and
cognitive
neuroscience
research

Review of
prior WJ,
WJ-R, WJ III
structural
validity
research

Copyright; Institute for Applied
Psychometrics; K.McGrew 1-23-14

Most
plausible
and best
fitting
odel?

CFA of MG model
result from MD (A)
sample in MCV (B)
sample(s)
Yes

Structural validity method comparisons across 7
intelligence batteries
EFA

Other exp.
methods

CFA

Cross-validation

WJ III

No

No

Yes

No

SB5

No

No

Yes

No

DAS-II

No

No

Yes

No

KABC-II

No

No

Yes (in “exploratory
manner”)

No

WAIS-IV

No

No

Yes

No

WISC-IV

Yes

No

Yes

Yes: Factor score (7)
congruence in random CV
sample of 440

WJ IV

Yes

Yes: MDS
and cluster
analysis

Yes: Exploratory
model generating
CFA (MD samples)
and CV CFA (CV
samples)

Yes: Randomly split
samples at six age groups.
CV of final MD models in
CV sample

Test

A

99.5 % of test
and latent
factor loadings
crossvalidated
(were
significant in
all agedifferentiated
samples crossvalidation B
samples)
!!!!!!

98.6 % of test
and latent
factor
loadings
crossvalidated
(were
significant in
all agedifferentiated
samples
crossvalidation B
samples) !!!!!!

B

Two final WJ IV cross-validated models across age groups: A = Broad CHC top-down model; B = Broad+narrow CHC bottom-up model

Five primary design principles have resulted in the
WJ IV COG GIA being significantly different in
composition than the WJ III COG GIA-Std.
1. Be the best factor indicators of each CHC broad domain

2. Be the best predictors of achievement from each CHC broad domain

3. Be the most cognitively complex indicators
from each CHC broad domain
4. Be the best measures of g (general intelligence) from each CHC broad
domain
5. Collectively should have a relatively equal balance of type of stimulus
characteristics (verbal, numeric, figural)
(Note: Trade-offs between the four design objectives were sometimes
necessary)

Two primary methods for measuring cognitive complexity of tests

Spatial position
from center of MDS
Guttman radex
analysis “maps”
g-loadings based on
factor/principal
component analysis

g

T1

T2

T3

T4

T5

T6

T7

T8

T9 T10 T11 T12

(1a) Spearman’s general Factor model


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
other tests. The
center
represents the
most cognitively
complex tests

2

The MDS “distance
metrics” were saved.

The calculation of a distance-based “relative cognitive
complexity” (rCC) metric for COG/OL tests
GENINF
SENREP

1

SNDBLN

NWDREP

COG test closest to
center (Phonological
Processing)
identified.

McGrew 02-04514

PICVOC
HUM
SCI

SOC

ORLRDG

WRDATK

SEGMNT

RDGVOC

ORLCMP
STYREC
VRBANL
MEMWRD

VRBATN
SNDAWR
UNDDIR

0

EDIT
LWIDNT

WRTSMP
RDGREC

ORLVOC PSGCMP
SPELL
PHNPRO
SPLSND
NUMSEN
NUMSER
APPROB

CALC
SNRDFL

NUMMAT

MEMNAM

MTHFLU
SNWRFL
WRDFLU

CONFRM
VAL

VISUAL
OBJNUM

NUMREV

NUMPAT
LETPAT

ANLSYN

-1

RETFLU
VISCLO

COG
OL
ACH
Res.

PAIRCN

PICREC
RPCNAM

-2
-2

-1

0

1

2

The distance of all
other tests from
Phonological
Processing was
calculated so that
high values indicated
more relative
cognitive complexity
(rCC) and lower
values (PICREC)
indicated less rCC.

Guttman radex MDS of all WJ IV (and 4 research tests) in WJ IV norm sample (ages 6-90+)

PHNPRO-Ga
SNDAWR-Ga

2.10

MDS relative CC (rCC)

Correlation = .93; but correspondence
diverges as test become higher in g and
cognitive complexity

VRBATN-Gwm

1.55
NUMSER-Gf
NUMREV-Gwm
SEGMNT-Ga

ORLVOC-Gc

ORLCMP-Gc
UNDDIR-Gwm
CONFRM-Gf
OBJNUM-Gwm
PICVOC-Gc

SENREP-Gwm
STYREC-Glr

1.00

RETFLU-Glr
LETPAT-Gs
NUMPAT-Gs

0.45

VISUAL-Gf
ANLSYN-GF
MEMWRD-Gwm
SNDBLN-Ga

NWDREP-Ga

PAIRCN-Gs
RPCNAM-Glr
PICREC-Gv

-0.10
0.4

0.5

g-loading

0.6

0.7

Relationship between g-loadings and MDS-based relative
cognitive complexity (rCC) for WJ IV COG and OL tests

0.8

The Cognitive tests were evaluated on the basis of
four (of five total) quantifiable COG design criteria
Real data augmented by Siskel and Ebert informal
rating system



Average CHC factor loadings



Average achievement correlation across domains




Average degree of g-loadings
Average degree of relative cognitive complexity
(Average across ages 6-90+)


Author/expert
CHC narrow factor
classifications

Comprehension – Knowledge
(Gc)

Lexical Knowledge
(VL)

Language
Development (LD)

PICVOC (Voc. ClusterLD/VL)

* Test in GIA

ORLVOC*

  

McGrew 2-04-14

General Information
(K0)

(Gc cluster) GENINF

COG Test 2: Number Series
• Was in WJ III Diagnostic Supplement
• Gf-RQ (Quantitative Reasoning)
• Not a “controlled learning” test as are Concept
Formation (Gf-I) and Analysis-Synthesis (Gf-RG)
• More Gf “in the wild” – without examiner
provided scaffolding
• Extensive history as a premier Gf test in the
psychometric measurement of intelligence
• High in cognitive complexity and g. Best single test
predictor of achievement. Best indicator of Gf factor.
• In GIA, BIA, Gf-Gc Composite, Gf, Gf3, Quantitative
Reasoning (RQ), and one Math Aptitude clusters.

COG Test 2: Number Series
The examinee is
presented with a series
of numbers with one
number missing in the
series. The examinee
must determine the
missing number.


One of
the most
frequent
Gf
variables
found in
Carroll’s
1993
seminal
review

McGrew 01-23-14


Number Series: Extensive history as a
premier Gf test in the psychometric
measurement of intelligence


Extensive research literature that has investigated the
nature of Number Series tests

Author/expert
CHC narrow
factor
classifications

Fluid Reasoning
(Gf)

Quantitative
Reasoning (RQ)

NUMSER*



Induction
(I)

(Gf cluster) CONFRM

 

General Sequential
Reasoning (RG)

(Gf3
cluster)

(Quantitative Reasoning Cluster-RQ)
* Test in GIA

McGrew 2-04-14

ANLSYN



COG Test 3: Verbal Attention
• Measure of Gwm (working memory-WM; attentional
control-AC)
• More ecological “real world” valid measure of
working memory
• High in cognitive complexity and g. Within Gwm,
the most cognitively complex, one of best
indicators of Gwm factor, and best predictor
of achievement
• In GIA, BIA, Gwm, Gwm3, Cognitive Efficiency, and one
Reading and 1 Written Language Aptitude clusters.

COG Test 3: Verbal Attention

(Sample items deleted
for test security
reasons)

In addition to
working memory
(WM), task requires
attentional control
(AC: controlled
executive function;
aka, focus)

Author/expert
CHC narrow
factor
classifications

Short-Term Working
Memory (Gwm)

Attentional Control
(AC)

VRBATN*

Memory Span
(MS)

Working Memory
(WM)

NUMREV

   cluster)
(Gwm



OBJNUM



(Gwm3 cluster)
* Test in GIA

McGrew 2-04-14



MEMWRD
(Auditory Memory
Span Cluster-MS)

SENREP

COG Test 4: Letter-Pattern
Matching
• Measure of Gs (perceptual speed) and orthographic
processing
• This speeded test (all WJ IV speeded tests) is based on a new
rate-based method of scaling the scores that eliminates the
need for bonus points
• Within Gs, it matches Number Pattern Matching in
g, Gs factor loading, and prediction of achievement. Is
more cognitively complex than Number Pattern Matching
• In GIA, Gs, Perceptual Speed (P), Cog. Eff. and Cog. clusters

COG Test 4: Letter-Pattern
Matching

(Sample items deleted
for test security
reasons)

Examinee locates
and circles the two
identical letter
patterns in a row of
six patterns in the
Response Booklet

Short-Term Working
Memory (Gwm)

Cognitive Processing Speed
(Gs)

Author/expert
CHC narrow
factor
classifications

Perceptual
Speed (P)

LETPAT*

  

Attentional
Control

NUMPAT



PAIRCN



(Gs cluster)
(Perceptual Speed
cluster-P)
McGrew 2-04-14

* Test in GIA

Long-Term Retrieval
(Glr)

Meaningful
Memory (MM)

Associative
Memory (MA)

STREC* (Glr cluster)

 

VAL





Author/expert
CHC narrow
factor
classifications

Speed of Lexical
Access (LA)

RPCNAM (Speed RETFLU

* Test in GIA
McGrew 2-04-14

of Lexical
Access
cluster-LA)

OL Test 3: Segmentation

•
•
•
•
•

Ga (PC)
Examinee listens to words and identifies word parts
In OL Phonetic Coding (PC) cluster
Highest loading test on Ga factor across all ages
A moderate measure of g and predictor of ach. across
all ages; much more so (and more cognitively complex)
than Sound Blending.
• Such tasks have been reported to be strong predictors
of early reading (Bouwmeester et al, 2011; Geuden &
Sandra, 2003)

OL Test 3: Segmentation


Short-Term Working
Memory (Gwm)

Auditory
Processing (Gs)

Author/expert
CHC narrow
factor
classifications

PHNPRO*



Memory for
Sound Patterns (UM)

Phonetic
Coding (PC)

SEGMNT

SNDBLN

(Phonetic Coding cluster-PC)

(Ga cluster)
* Test in GIA
McGrew 2-04-14

NWDREP

COG Test 7: Visualization
• Measure of Gv-Visualization (Vz)
•Visualization consists of two subtests that each
measure Gv-Vz (visualization) via tasks that vary on
task complexity and degree of “minds eye” (mental
rotation) manipulations
• Within Gv, highest on cognitive complexity, g, Gv
factor, and prediction of achievement
• In GIA, Gv and both Math Aptitude clusters

COG Test 7A: Visualization-Spatial
Relations


Examinee identifies the two or three pieces that form a
complete target shape

COG Test 7B: Visualization-Block
Rotation
• Gv-Vz (Visualization)
• Based on classic “mental rotation” tasks (e.g.,
Shepard& Metzlar; Vandenberg)


Examinee identifies the two block patterns that match
the target pattern, but have been rotated in space

COG Test 7B: Visualization-Block
Rotation
• Gv-Vz (Visualization)
• Based on classic “mental rotation” tasks (e.g., Shepard
& Metzlar; Vandenberg)

Author/expert
CHC narrow
factor
classifications

Visual Processing
(Gv)

Visualization
(Vz)

Visual Memory
(MV)

VISUAL*



(Gv cluster)

* Test in GIA
McGrew 2-04-14

PICREC

WJ IV COG Scholastic Aptitude (SAPT) Clusters:
Primary design considerations
Back to the future: The SAPT concept is not new. SAPT’s were included in the WJ
and WJ-R; they were replaced with the Predicted Achievement option in the WJ III.
Each WJ IV COG SAPT cluster score is based on a combination of four tests that
together produce the most efficient and strongest prediction for the selected
achievement area.
The SAPTs are the combination of WJ IV COG tests that are the most highly
correlated with each curricular area as identified statistically (multiple regression);
consideration was also given to relevant theory and the extant research literature
(e.g., McGrew & Wendling,2010).
Some tests were eliminated as possible predictor tests (e.g., Number Series) if there
was clear predictor-criterion contamination (e.g., Math Problem Solving cluster
includes Number Matrices).
Each SAPT must include four tests that are each from different CHC broad ability
domains.
Copyright, Institute for Applied
Psychometrics, K.McGrew; 01-23-14

Clarification of Ability Construct Terminology


Ability
“as used to describe an attribute of individuals, ability refers to the possible
variations over individuals in the liminal levels of task difficulty (or in derived
measurements based on such liminal levels) at which, on any given occasion in
which all conditions appear favorable, individuals perform successfully on a
defined class of tasks” (p. 8, italics in original).
“every ability is defined in terms of some kind of performance, or potential for
performance (p. 4).”

Cognitive Abilities
Abilities on tasks “in which correct or appropriate processing of mental
information is critical to successful performance” (p. 10; italics in original).
Achievement abilities

“refers to the degree of learning in some procedure intended to produce
learning, such as an informal or informal course of instruction, or a period of
self study of a topic, or practice of a skill” (p. 17). As noted by Carroll (1993)

Abilities
Cognitive Abilities

Achievement Abilities
General
Intelligence (g)
Quantitative
Knowledge
(Gq)

Comp Knowledge
(Gc)

Fluid
Reasoning (Gf)

Short-Term
Memory (Gsm)

Long-Term
Storage &
Retrieval (Glr)

Visual
Processing
(Gv)

Auditory
Processing
(Ga)

Speed (Gs)

Etc.

Reading &
Writing (Grw)

Etc.

Etc.

Etc.

Etc.

Etc.

Etc.

Processing

Rdg
Apt
Math
Apt

Etc.

Etc.

Ach. domaingeneral apt.
Ach. domainspecific apt.


Vertical columns represent abilities, factors or latent traits
(primarily factor-analysis derived internal structural validity
constructs)
Horizontal arrow rows represent aptitudes (primarily multiple
regression derived external [predictive] validity constructs)

Conceptual distinction between Abilities: Cognitive abilities,
achievement abilities, and aptitudes (McGrew, in press b)

WJ IV Scholastic Aptitude Cluster Organization
Gf

Concept
Formation
(I)

Gc

Gwm

Oral
Vocabulary
(LD/VL)

Oral
Vocabulary
(LV/VL)

Number
Series
(RQ)

Oral
Vocabulary
(LD/VL)

Verbal
Attention
(WM)

Num Pattern
Matching
(P)

Num Pattern
Matching
(P)

WJ IV Ach Clusters
Reading
Broad Reading
Reading Comp
Reading Comp-Ext
Reading Fluency
Reading Rate

Phonological
Processing
(PC)

Basic Rdg Skills
Writing
Broad Writing
Written Expression

Story
Recall
(MM)

Basic Writing Skills

Visualization
(Vz)

Math
Broad Math
Math Calc Skills

Visualization
(Vz)

Pair
Cancellation
(P/EF)

Numbers
Reversed
(WM)

Gv

Phonological
Processing
(PC)

Phonological
Processing
(PC)

Glr

Phonological
Processing
(PC)

Num Pattern
Matching
(P)

Verbal
Attention
(WM)

Oral
Vocabulary
(LD/VL)

AnalysisSynthesis
(RG/RQ)

Ga

Num Pattern
Matching
(P)

Oral
Vocabulary
(LV/VL)
Oral
Vocabulary
(LD/VL)

Gs

Math Prob Solving

Grw/Gq domain general
Grw domain specific
Gq domain specific


Scholastic Aptitude Clusters: Potential Uses
•
•
•
•
•
•

Designed to predict near term academic performance
Time efficient referral-focused selective testing
Time efficient academic domain-specific screening
Time efficient annual review evaluations
Gifted and talented screening – domain-specific talents?
May be useful in estimating quickness of response to
intervention
• Provide information regarding the concept of “expected
underachievement”
• Formulation of differential academic domain expectations
• ?

CHC achievement
abilities and WJ IV clusters

CHC cognitive abilities and WJ IV scholastic aptitude cognitive clusters

Gf

Gc

Gwm

Gs

Ga

Glr

Gv

Gq

Grw
Reading

Rdg. Cmp.

Rdg. Apt. A
(Predictor Score)
Regression-based prediction models that
account for regression-to-the-mean

Brd. Rdg.
Rdg. Flu.

Rdg Cmp. Ex

Rdg. Rate

Rdg. Apt. B
(Predictor Score)

Bas. Rdg. Sk.
Wr. Lng.

WL. Apt. A
(Predictor Score)

Brd. Wr. Lg.

Wr. Exp.

WL. Apt. B
(Predictor Score)

Bas. Wr. Sk.
Math.

Math Apt. A
(Predictor Score)

Brd. Math

Math Cal.Sk.
Math Apt. B
(Predictor Score)

Predicted
Target Cluster
Score

Math Pr. Slv.

(minus)

(See Table 1-10 for the specific tests and
cluster information)

Scholastic Aptitude/Achievement comparison procedures

Actual Target
Cluster Score

Difference
Score

(equals)

(Compare to distribution of difference
scores in WJ IV norm sample to
determine significant strength or
weakness)
SD and PR for specified
SD cut-off score

Additional select technical and
psychometric information
(McGrew, LaForte, Schrank, 2014)
Dr. Kevin McGrew
Institute for Applied Psychometrics (IAP)


National Norm Sample
• 7,416 participants
• Preschool (664)
• K-12 (3,891)
• College/University (775)

• Adult (2,086)

• Ages 2-90+ years, Grades K.0-18.0
• 100 geographically diverse communities from 46 states and the
District of Columbia
• The Standards for Educational and Psychological Testing (aka., the
Joint Standards) (American Psychological Association, American
Educational Research Association, & National Council on
Measurement in Education, 1999; in press) guided the norming
and technical analysesCopyright; Institute for Applied

Sources of validity
evidence presented
•Representativeness of the WJ IV Test Content, Process, and
Construct Coverage
•Developmental Patterns of WJ IV Ability Clusters
•Internal Structure and Relations within the WJ IV
•Relationship of WJ IV Scores to Other Measures of Cognitive
Abilities, Oral Language, and Achievement
•Performance of Clinical Samples on WJ IV Measures

Dr. Kevin McGrew internet resources

(@iqmobile)

WJ IV NASP 2014 workshop: Cognitive and Oral Language batteries by Dr. Kevin McGrew

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