Assessing the Incremental Value of Kabc-Ii Luria Model Scores in Predicting Achievement: What Do They Tell Us Beyond the Mpi?

McGill, Ryan J.; Spurgin, Angelia R.

doi:10.1002/pits.21940

Cited by 40 publications

(14 citation statements)

References 50 publications

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“…Whereas, related predictive validity studies with cognitive measures (e.g., Benson, Kranzler, & Floyd, 2016;Canivez, 2013a;McGill, 2015aMcGill, , 2015bMcGill & Spurgin, 2016) have largely suggested that broad and narrow cognitive abilities account for trivial portions of achievement after controlling for general ability, the present results suggest that this conclusion as a general rule may be overstated. As previously mentioned, although the GIA consistently accounted for large reading effects, lower-order scores accounted for meaningful incremental prediction in several circumstances.…”

Section: Discussioncontrasting

confidence: 51%

“…Incremental validity studies using HMRA have been conducted previously on the WJ III COG (McGill, 2015a;McGill & Busse, 2015) and other related intelligence tests (e.g., Canivez, 2013a;McGill, 2015b;McGill & Spurgin, 2016). Across these studies, it was consistently demonstrated that the omnibus full scale IQ score accounted for most of the reliable achievement variance that could be predicted in the regression models and that little additional incremental variance was accounted for by the lower-order broad and narrow ability scores after controlling for the predictive effects of the general factor.…”

Section: Introductionmentioning

confidence: 90%

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Re(Examining) Relations between CHC Broad and Narrow Cognitive Abilities and Reading Achievement

McGill¹

2017

JEDP

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Previously, Evans and colleagues (2001) utilized simultaneous multiple regression to examine relations between Cattell-Horn-Carroll (CHC;Schneider & McGrew, 2012) broad and narrow cognitive abilities and reading achievement across the school age span. Although their findings suggest that many broad/narrow abilities had clinically significant effects on reading achievement they failed to account for the potential moderating effects of the general factor. To account for these effects, the current study employed hierarchical multiple regression analysis to reexamine the relationships between CHC dimensions and reading achievement after controlling for the effects of the general factor with 4,722 participants ages 6-18 from the Woodcock Johnson III Psychoeducational Battery (WJ III; Woodcock, McGrew, & Mather, 2001a). Results from the present study indicate that the full scale GIA composite (as a proxy for g) consistently accounted for large effects across the school age span for all of the reading achievement variables that were assessed. Among the broad and narrow abilities, only Gc consistently accounted for meaningful proportions of reading scores beyond g. As a consequence, researchers are encouraged to give greater consideration to the dimensionality of broad and narrow CHC measures when examining cognitive-achievement relationships or they may risk over-interpreting the predictive effects associated with these indices. Potential implications for clinical application of CHC theory are also discussed.

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Section: Discussioncontrasting

confidence: 51%

Section: Introductionmentioning

confidence: 90%

Re(Examining) Relations between CHC Broad and Narrow Cognitive Abilities and Reading Achievement

McGill¹

2017

JEDP

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“…We did observe relationships between temporal variability of FCN and mental processing scale, which combines both sequential and simultaneous processing scales and is a measure of a child's overall level of cognitive processing McGill and Spurgin (2016). Interestingly, we observed that for the mental processing scale, both positive and negatively correlated network dynamics are important to distinguish between low and high-scoring children.…”

Section: Age-related Increase In Temporal Variabilitymentioning

confidence: 69%

Linking flexibility of brain networks to cognitive development in preschool children

Chamakura

Daimi

Watanabe³

et al. 2020

Preprint

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Recent studies of functional connectivity networks (FCNs) suggest that the reconfiguration of brain network across time, both at rest and during task, is linked with cognition in human adults. In this study, we tested this prediction, i.e. cognitive ability is associated with a flexible brain network in preschool children of 3-4 years -a critical age, representing a 'blossoming period' for brain development. We recorded magnetoencephalogram (MEG) data from 88 preschoolers, and assessed their cognitive ability by a battery of cognitive tests. We estimated FCNs obtained from the source reconstructed MEG recordings, and characterized the temporal variability at each node using a novel path-based measure of temporal variability; the latter captures reconfiguration of the node's interactions to the rest of the network across time. Using connectome predictive modeling, we demonstrated that the temporal variability of fronto-temporal nodes in the dynamic FCN can reliably predict out-of-scanner performance of short-term memory and attention distractability in novel participants. Further, we observed that the network-level temporal variability increased with age, while individual nodes exhibited an inverse relationship between temporal variability and node centrality. These results demonstrate that functional brain networks, and especially their reconfiguration ability, are important to cognition at an early but a critical stage of human brain development.

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“…Whereas a series of recent exploratory investigations failed to support the structural and predictive validity of Luria dimensions on the KABC‐II (e.g., McGill & Spurgin, , ), these studies were not dispositive for determining what psychological dimensions are measured by the Luria model. Accordingly, the purpose of the present study was to examine the structural validity of the Luria interpretive model across the school age (ages 7–18) using rival CFA procedures in an attempt to better disclose the latent structure of the Luria subtest configuration.…”

Section: Discussionmentioning

confidence: 95%

Exploring the latent structure of the Luria model for the KABC‐II at school age: Further insights from confirmatory factor analysis

McGill

2017

Psychology in the Schools

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The present study examined the factor structure of the Luria interpretive model for the Kaufman Assessment Battery for Children-Second Edition (KABC-II) with normative sample participants aged 7-18 (N = 2,025) using confirmatory factor analysis with maximumlikelihood estimation. For the eight subtest Luria configuration, an alternative higher-order model with Pattern Reasoning being permitted to cross-load on the Planning and Simultaneous Processing factors provided the best fit to the normative sample data. Variance apportionment suggests that additional consideration, beyond the omnibus Mental Processing Index, of the contribution of the firstorder factor-based scores (i.e., SQ, SM, P, and L), and in some cases the individual subtests themselves, may be warranted. Implications for clinical interpretation and the anticipated normative update of the measurement instrument are discussed.

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Assessing the Incremental Value of Kabc-Ii Luria Model Scores in Predicting Achievement: What Do They Tell Us Beyond the Mpi?

Cited by 40 publications

References 50 publications

Re(Examining) Relations between CHC Broad and Narrow Cognitive Abilities and Reading Achievement

Re(Examining) Relations between CHC Broad and Narrow Cognitive Abilities and Reading Achievement

Linking flexibility of brain networks to cognitive development in preschool children

Exploring the latent structure of the Luria model for the KABC‐II at school age: Further insights from confirmatory factor analysis

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