Research Byte: An investigation of the structural #validity of the #WISCV #ancillary scores - #IQ #intelligence #Wechsler #WISC-V #factoranalysis #schoolpsychology

 Another open access research article that can be downloaded by clicking here.

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Research Byte: Age-related change in #inhibitory processes when controlling for #workingmemory (#Gwm) capacity and #processingspeed (#Gs) - #cognition #intelligence #CHC #executivefunctions #Gwm #Gs #schoolpsychology

 

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This is a nice study/paper.  And it is open access and can be downloaded for reading by clicking here.

I recommend reading, if not the entire article, at least the introductory lit review.  The introductory lit review is worth a read if one wants to understand the basic literature re the definition, theories, and research regarding the relations between cognitive inhibition, working memory capacity (Gwm), and processing speed (Gs) in a developmental context.  

Abstract

The main purpose of this study was to examine the age-related changes in inhibitory control of 450 children at the ages of 7–8, 11–12, and 14–16 when controlling for working memory capacity (WMC) and processing speed to determine whether inhibition is an independent factor far beyond its possible reliance on the other two factors. This examination is important for several reasons. First, empirical evidence about age-related changes of inhibitory control is controversial. Second, there are no studies that explore the organization of inhibitory functions by controlling for the influence of processing speed and WMC in these age groups. Third, the construct of inhibition has been questioned in recent research. Multigroup confirmatory analyses suggested that inhibition can be organized as a one-dimension factor in which processing speed and WMC modulate the variability of some inhibition tasks. The partial reliance of inhibitory processes on processing speed and WMC demonstrates that the inhibition factor partially explains the variance of inhibitory tasks even when WMC and processing speed are controlled and some methodological concerns are addressed.

Occam’s razor and human #intelligence (and #cognitive ability tests)….yes…but sometimes no…food for thought for #schoolpsychologists

 

“Occam's razor (also spelled Ockham's razor or Ocham's razor; Latin: novacula Occami) is the problem-solving principle that recommends searching for explanations constructed with the smallest possible set of elements. It is also known as the principle of parsimony or the law of parsimony (Latin: lex parsimoniae)”

In the context of fitting structural CFA models to intelligence test data, it can be summarized as “given two models with similar fit to the data, the simpler model is preferred” (Kline, 2011, p. 102).” The law of parsimony is frequently invoked in research articles when an investigator is faced with competing factor models regarding the underlying structure of a cognitive ability test battery. However, when complex human behavior is involved, especially something as complex as human intelligence and the brain, it is possible that Occam’s razor might interfer with a thourough understanding of human intelligence and test batteries designed to measure intelligence. The following quote2note has stuck with me as an important reminder that when faced with alternative and more complex statistical CFA models, these models should not be summarily dismissed based only on the parsimony principle. As stated by Stankov, Boyle, and Cattell (1995)

“while we acknowledge the principle of parsimony and endorse it whenever applicable, the evidence points to relative complexity rather than simplicity…the insistence on parsimony at all costs can lead to bad science” (p. 16).

Stankov, L., Boyle, G. J., & Cattell, R. B. (1995). Models and paradigms in personality and intelligence research. In D. Saklofske & M. Zeidner (Eds.), International handbook of personality and intelligence (pp. 15–43). New York, NY: Plenum Press.

CFA of WISC-V: A five factor CHC battery

There are dueling factor study articles regarding the WISC-V in the research literature. Here is the take of Reynolds and Keith, who, IMHO, tend to do some of the best factor structure research in intelligence testing.

The five factors look like clear Gc, Gv, Gf, Gwm and Gs CHC factors.

Abstract

The purpose of this research was to test the consistency in measurement of Wechsler Intelligence Scale for Chil-dren-Fifth Edition (WISC-V; Wechsler, 2014) constructs across the 6 through 16 age span and to understand the constructs measured by the WISC-V. First-order, higher-order, and bifactor confirmatory factor models were used. Results were compared with two recent studies using higher-order and bifactor exploratory factor analysis (Canivez, Watkins, & Dombrowski, 2015; Dombrowski, Canivez, Watkins, & Beaujean, 2015) and two using con-firmatory factor analysis (Canivez, Watkins, & Dombrowski, 2016; Chen, Zhang, Raiford, Zhu, & Weiss, 2015). We found evidence of age-invariance for the constructs measured by the WISC-V. Further, both g and five distinct broad abilities (Verbal Comprehension, Visual Spatial Ability, Fluid Reasoning, Working Memory, and Processing Speed) were needed to explain the covariances among WISC-V subtests, although Fluid Reasoning was nearly equivalent to g. These findings were consistent whether a higher-order or a bifactor hierarchical model was used, but they were somewhat inconsistent with factor analyses from the prior studies. We found a correlation between Fluid Reasoning and Visual Spatial factors beyond a general factor (g) and that Arithmetic was primarily a direct indicator of g. Composite scores from the WISC-V correlated well with their corresponding underlying factors. For those concerned about the fewer numbers of subtests in the Full Scale IQ, the model implied relation between g and the FSIQ was very strong.

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WISC-V CFA by Reynolds and Keith - a MUST read by two of the best intelligence test scholars I know

Intelligence

Available online 3 March 2017

In Press, Corrected Proof — Note to users

Multi-group and hierarchical confirmatory factor analysis of the Wechsler Intelligence Scale for Children—Fifth Edition: What does it measure? ^☆

• Matthew R. Reynolds^{a, ,} ,
• Timothy Z. Keith^b

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http://dx.doi.org.ezp1.lib.umn.edu/10.1016/j.intell.2017.02.005

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Highlights

•

WISC-V constructs are measured similarly across the 6–16-year age range.

•

g and five broad ability factors account for subtest covariances.

•

Our CFA findings diverged from EFA research.

•

g is measured strongly in the new 7 subtest FSIQ.

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Abstract

The purpose of this research was to test the consistency in measurement of Wechsler Intelligence Scale for Children-Fifth Edition (WISC-V; Wechsler, 2014) constructs across the 6 through 16 age span and to understand the constructs measured by the WISC-V. First-order, higher-order, and bifactor confirmatory factor models were used. Results were compared with two recent studies using higher-order and bifactor exploratory factor analysis (Canivez, Watkins, & Dombrowski, 2015; Dombrowski, Canivez, Watkins, & Beaujean, 2015) and two using confirmatory factor analysis (Canivez, Watkins, & Dombrowski, 2016; Chen, Zhang, Raiford, Zhu, & Weiss, 2015). We found evidence of age-invariance for the constructs measured by the WISC-V. Further, both g and five distinct broad abilities (Verbal Comprehension, Visual Spatial Ability, Fluid Reasoning, Working Memory, and Processing Speed) were needed to explain the covariances among WISC-V subtests, although Fluid Reasoning was nearly equivalent to g. These findings were consistent whether a higher-order or a bifactor hierarchical model was used, but they were somewhat inconsistent with factor analyses from the prior studies. We found a correlation between Fluid Reasoning and Visual Spatial factors beyond a general factor (g) and that Arithmetic was primarily a direct indicator of g. Composite scores from the WISC-V correlated well with their corresponding underlying factors. For those concerned about the fewer numbers of subtests in the Full Scale IQ, the model implied relation between g and the FSIQ was very strong.

Research Byte: Short-term memory for faces is related to general intelligence: A possible new CHC narrow ability taxonomy candidate?

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Intelligence

Available online 21 May 2016

In Press, Corrected Proof — Note to users

Short-term memory for faces relates to general intelligence moderately ^☆

• Gilles E. Gignac^, ,
• Mahesh Shankaralingam,
• Kipling Walker,
• Philippe Kilpatrick

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doi:10.1016/j.intell.2016.05.001

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---

Highlights

•

Short-term memory for faces correlated positively with several stratum II factors.

•

Short-term memory for faces was associated with general intelligence at .34.

•

Short-term memory for faces should not be considered “special” (i.e., independent of g).

•

Prosopagnosia may be best characterised as a learning disability.

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Abstract

The results associated with a small number of investigations suggest that individual differences in memory for faces, as measured by the Cambridge Face Memory Test (CFMT), are independent of intelligence. Consequently, memory for faces has been suggested to be a special construct, unlike other cognitive abilities. However, previous investigations have measured intelligence with only one or two subtests. Additionally, the sample sizes upon which previous investigations were based were relatively small (N = 45 to 80). Consequently, in this investigation, a battery of eight cognitive ability tests and the CFMT were administered to a relatively large number of participants (N = 211). Based on a correlated-factor model, memory for faces was found to be correlated positively with fluid intelligence (.29), short-term memory (.23) and lexical knowledge ability (.19). Additionally, based on a higher-order model, memory for faces was found to be associated with g at .34. The results are interpreted to suggest that memory for faces, as measured by the CFMT, may be characterised as a relatively typical narrow cognitive ability within the Cattell–Horn–Carroll (CHC) model of intelligence, rather than a special ability (i.e., independent of other abilities). Future research with a greater diversity in the measurement of face recognition ability is encouraged (e.g., long-term memory), as the CFMT is a measure of short-term face memory ability.

Keywords

• Intelligence;
• CHC theory;
• Face identity recognition;
• Prosopagnosia

Recommended stat book: Multiple Regression & Beyond by Dr. Tim Keith

I was pleased to learn that one of the most respected quantoids I know has revised his classic book, Multiple Regression and Beyond:  An Introduction to Multiple Regression and Structural Equation Modeling.    Dr. Keith's quantitative skills are top notch.   He is one of three quantoids I consult when I need advice.  Tim has an uncanny talent for making statistical concepts understandable. 

Two big thumbs up for Tim's new edition.  Additional information (including link to Amazon) can be found at his web page.

Video tutorial: Estimating latent WISC-IV and WAIS-IV scores for individuals--Dr. Joel Schneider

Dr. Joel Schneider has done it again.  A brilliant video tutorial demonstrating how latent factor scores can be used, via Excel templates he provides, to interpret scores on the WISC-IV and WAIS-IV.  This is complex material but his beautiful visual video tutorial makes it easier to understand the complex constructs.  Dr. Schneider continues to push the envelope on psychometric based IQ test score interpretation.

Research Byte: CHC and convergence in cognitive assessment

 

 

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Research byte: WISC-IV index score invariance in normal and clinical groups

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Dissertation Dish: CFA of WJ III AND SB5 IQ tests in a preschool population

Joint confirmatory factor analysis of the Woodcock-Johnson Tests of Cognitive Abilities, Third Edition, and the Stanford-Binet Intelligence Scales, Fifth Edition, with a preschool population by Chang, Mei, Ph.D., Ball State University, 2011 , 126 pages; AAT 3466801

Abstract

Significant evidence from the legislation, medical/clinical, or professional practice perspective all points to the advantages and necessity of conducting comprehensive assessment of cognitive abilities, especially in young children, to identify cognitive deficits, arrive at an accurate diagnosis, and establish bases for developing interventions and recommending services. Cross-battery assessment approach provides school psychologists a useful tool to strengthen their preferred cognitive battery by adopting and comparing subtests from other batteries to build up a comprehensive and theoretically sound evaluation of an individual's cognitive profile to increase the validity of test interpretation. Using joint confirmatory factor analysis, this study explored the combined underlying construct validity of the Woodcock-Johnson Tests of Cognitive Abilities, Third Edition (WJ-III COG) and the Stanford-Binet Intelligence Scales, Fifth Edition (SB5) with an independent sample of preschool children. Seven models were examined and the results showed that relatively, the underlying construct of the two tests was best represented by a three-stratum alternative CHC model in which the Gf factor and subtests had been removed. This indicates that not all the CHC constructs shared by both tests can be reliably identified among young children. Constructs of the CHC theory may be represented differently on preschool cognitive batteries due to developmental influences. Although WJ-III COG and SB5 tests as a whole did not demonstrate good results for purposes of cross-battery assessment, certain subtests (e.g., subtests representing crystallized intelligence) from each battery offer interpretative value for individual broad ability factors, providing school psychologists an in-depth understanding of a preschooler's crystallized knowledge. Exploratory factor analyses were conducted with subtests from WJ-III COG and SB5 representing the four shared broad factors ( Gc, Gf, Gv, and Gsm ). Results revealed that a 4-factor solution is a better model fit to the data. Future research includes recruiting young children with disabilities or special needs to explore best representative underlying construct of combined WJ-III COG and SB5, allowing for cross-battery assessment



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Research Bytes: Bi-factor item factor analysis and CFA model fit/misfit

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Research byte: Are reading,listening and video comprehension tasks measuring the same comprehension construct?

As per usual when I make a research byte/brief post, if anyone would like to read the original article, I can share via email---with the understanding that the article is provided in exchange for a brief guest post about it's contents. :) (contact me at iap@earthlink.net if interested). Also, if figure/images are included in the post, they can usually be made larger by clicking on the image.

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intelligence IQ tests IQ scores CHC theory Cattell-Horn-Carroll human cognitive abilities psychology school psychology individual differences cognitive psychology neuropsychology special education educational psychology psychometrics psychological assessment psychological measurement IQs Corner neuroscience neurocognitive cognitive abilities cognition Listening comprehension Reading comprehension Video comprehension

Dissertation Dish: Dimensionality of processing speed tests

Exploring the relationships among various measures of processing speed in a sample of children referred for psychological assessments by Nelson, Megan A., Ph.D., University of Virginia, 2009, 102 pages; AAT 3348732

Abstract (Summary)

Processing speed is a robust psychometric factor in modern tests of cognitive ability (Carroll, 1993), but the common factors underlying mental speed and its contributions to individual differences in functioning are not well understood. The goal of the current study was to further explore mental speed by conducting a confirmatory factor analysis (CFA) on 11 speeded subtest scores. It was hypothesized that the 11 subtests would be best represented by a four-factor model. These four factors were then submitted to a cluster analysis to identify whether certain patterns of factor scores were related to different demographic characteristics, diagnoses, or referral questions. It was hypothesized that Learning Disorder, Attention-Deficit/Hyperactive Disorder, and comorbid LD/ADHD diagnoses would be most likely to have unique processing speed factor patterns.

Participants were 186 children (ages 6 - 18 years old) referred to a university-based clinic for a comprehensive psychological evaluation. The CFA indicated that although the 11 measures are all speeded, they are best represented as four distinct constructs, labeled perceptual speed, naming facility, academic facility, and reaction time in this study. The clusters produced in this study appeared to be most highly differentiated by level (likely influenced by intelligence level) and by pattern only in respect to reaction time factor scores. Therefore, both the CFA and cluster analyses lend support to Cattell-Horn-Carroll cognitive theory's distinction between cognitive processing speed (Gs) and decision/reaction time (Gt). Additionally, the CFA results suggest that Gs may be multifaceted, but the cluster analysis did not differentiate clusters based on the processing speed factors. Although the results of this study have important implications for both assessment clinicians and cognitive theory, further research is needed to clarify the constructs of processing speed and reaction time as well as to identify the clinical implications of different processing speed patterns.

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