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
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".