A Psychometric Network Analysis of CHC Intelligence Measures: Implications for Research, Theory, and Interpretation of Broad CHC Scores “Beyond g”

Abstract

For over a century, the structure of intelligence has been dominated by factor analytic methods that presume tests are indicators of latent entities (e.g., general intelligence or g). Recently, psychometric network methods and theories (e.g., process overlap theory; dynamic mutualism) have provided alternatives to g-centric factor models. However, few studies have investigated contemporary cognitive measures using network methods. We apply a Gaussian graphical network model to the age 9–19 standardization sample of the Woodcock–Johnson Tests of Cognitive Ability—Fourth Edition. Results support the primary broad abilities from the Cattell–Horn–Carroll (CHC) theory and suggest that the working memory–attentional control complex may be central to understanding a CHC network model of intelligence. Supplementary multidimensional scaling analyses indicate the existence of possible higher-order dimensions (PPIK; triadic theory; System I-II cognitive processing) as well as separate learning and retrieval aspects of long-term memory. Overall, the network approach offers a viable alternative to factor models with a g-centric bias (i.e., bifactor models) that have led to erroneous conclusions regarding the utility of broad CHC scores in test interpretation beyond the full-scale IQ, g.

Carroll’s Three-Stratum (3S) Cognitive Ability Theory at 30 Years: Impact, 3S-CHC Theory Clarification, Structural Replication, and Cognitive–Achievement Psychometric Network Analysis Extension

“…Furthermore, comparisons of the current McGrew–Carroll 2003/2022 WJ III 46-test results (hereafter referred to as the MC analysis ) are only made with Carroll’s 29-test WJ-R analysis results (hereafter referred to as the Carroll analysis ), not with the 16-test analysis. Although my current and evolving views regarding psychometric and theoretical g are not 100% consistent with Carroll’s (see McGrew et al 2023 ), to the best of my ability, I present what I believe would be interpretations consistent with Carroll’s thinking of the MC analysis results. The final bifactor CFA model results are presented in Table 1 .…”

“…The most salient difference between the three related CHC theories is the presence (or absence) of a higher-order general intelligence factor or ability ( g ). Horn was a staunch anti- g proponent who believed that psychometric g was nothing more than an emergent property statistical abstraction ( McGrew et al 2023 )—it did not represent a true ability or mechanism in the human brain ( Horn 1998 ; Horn and Noll 1997 ; McArdle 2007 ; McArdle and Hofer 2014 ; Ortiz 2015 ). Conversely, Carroll was a staunch proponent of psychometric g as possibly representing some form of biological substrate present in individuals that influences the speed and efficiency of information processing ( Carroll 1991 , 1993 , 1996 , 2003 ).…”

“…Examples include the following Carroll statements in three publications after his seminal work “the question remains whether a unitary g exists, or whether a factorially produced g is merely a mathematical artifact ” ( Carroll 1998, p. 13 ; emphasis added); “What has not been adequately demonstrated and proven at this time is that g is a ‘true ability” independent of more specific cognitive abilities defined by various types of psychological tests and observations” ( Carroll 1997, p. 151 , emphasis added); the “continued psychological and even philosophical examination of the nature of factor g is a must ” ( Carroll 2003, p. 19 ). These statements suggest that Carroll was aware, but did not make it sufficiently clear, that much of the intelligence structural analyses research literature suffers from the problem of conflating psychometric and theoretical g ( Fried 2020 ; McGrew et al 2023 ).…”

“…One hypothesis is that the abilities measured by Picture Recognition (Gv-MV, visual memory) and Visual Closure (Gv-CS, closure speed) are considered minor Gv abilities ( Schneider and McGrew 2018 ). In the MC analysis, there were two stronger indicators (Spatial Relations and Block Rotation) of one of the major narrow abilities of Gv (visualization) ( McGrew et al 2014 ; McGrew et al 2023 ; Schneider and McGrew 2012 , 2018 ), as well as a test (Planning) hypothesized to measure the Gv narrow ability of Spatial Scanning (Gv-SS). 7 The MC analysis Gv factor may be a broader and more robust Gv factor than the Carroll analysis Gv factor.…”

“…People who do factor analysis by uncritical use of programs in computer packages run the risk of making fools of themselves” ( Carroll 1978, p. 91 ; emphasis added). It is my opinion that Carroll would still be dismayed by some of the EFA and CFA studies of intelligence tests published during the past two decades that often used narrow or restricted forms of factor analysis methods and rigid formal statistical rules for decision-making, with little attempt to integrate contemporary substantive research or theory to guide the analysis and interpretation of the results (e.g., see Decker 2021 ; Decker et al 2021 ; McGrew et al 2023 ).…”