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Record W2806733544 · doi:10.1111/bjep.12230

Construct validity of the Wechsler Intelligence Scale For Children – Fifth <scp>UK</scp> Edition: Exploratory and confirmatory factor analyses of the 16 primary and secondary subtests

2018· article· en· W2806733544 on OpenAlexaboutno aff
Gary L. Canivez, Marley W. Watkins, Ryan J. McGill

Bibliographic record

VenueBritish Journal of Educational Psychology · 2018
Typearticle
Languageen
FieldDecision Sciences
TopicPsychometric Methodologies and Testing
Canadian institutionsnot available
Fundersnot available
KeywordsWechsler Adult Intelligence ScaleWechsler Intelligence Scale for ChildrenPsychologyWechsler Preschool and Primary Scale of IntelligenceExploratory factor analysisConstruct validityConfirmatory factor analysisIntelligence quotientPsychometricsDevelopmental psychologyClinical psychologyStatisticsCognitionStructural equation modelingPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: ; Wechsler, 2016a, Wechsler Intelligence Scale for Children-Fifth UK Edition, Harcourt Assessment, London, UK) to guide interpretation. AIMS AND METHODS: was examined using complementary exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) for all models proposed by Wechsler (2016b, Wechsler Intelligence Scale for Children-Fifth UK Edition: Administration and scoring manual, Harcourt Assessment, London, UK) as well as rival bifactor models. SAMPLE: standardization sample (N = 415) correlation matrix was used in analyses due to denial of standardization sample raw data. RESULTS: EFA did not support a theoretically posited fifth factor because only one subtest (Matrix Reasoning) had a salient pattern coefficient on the fifth factor. A model with four group factors and a general intelligence factor resembling the Wechsler Intelligence Scale for Children - Fourth Edition (WISC-IV; Wechsler, 2003, Wechsler Intelligence Scale for Children-Fourth Edition, Psychological Corporation, San Antonio, TX, USA) was supported by both EFA and CFA. General intelligence (g) was the dominant source of subtest variance and large omega-hierarchical coefficients supported interpretation of the Full Scale IQ (FSIQ) score. In contrast, the four group factors accounted for small portions of subtest variance and low omega-hierarchical subscale coefficients indicated that the four-factor index scores were of questionable interpretive value independent of g. Present results replicated independent assessments of the Canadian, Spanish, French, and US versions of the WISC-V (Canivez, Watkins, & Dombrowski, 2016, Psychological Assessment, 28, 975; 2017, Psychological Assessment, 29, 458; Fennollar-Cortés & Watkins, 2018, International Journal of School & Educational Psychology; Lecerf & Canivez, 2018, Psychological Assessment; Watkins, Dombrowski, & Canivez, 2018, International Journal of School and Educational Psychology). CONCLUSION: should be of the FSIQ as an estimate of general intelligence.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.034
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.327
GPT teacher head0.468
Teacher spread0.141 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations44
Published2018
Admission routes1
Has abstractyes

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