Reliability and factorial validity of the Canadian Wechsler Intelligence Scale for Children–Fifth Edition
Bibliographic record
Abstract
The reliability and factorial validity of the Wechsler Intelligence Scale for Children–Fifth Edition: Canadian (WISC-VCDN) was investigated. The higher-order model preferred by Wechsler (2014b) contained five group factors but lacked discriminant validity. An alternative bifactor model with four group factors and one general factor, akin to the traditional Wechsler model, exhibited the best global fit. The general factor accounted for 33.8% of the total variance and 67.6% of the common variance, but none of the group factors accounted for substantial portions of variance. All together, the general and group factors accounted for 50% of the total variance. Omega reliability coefficients demonstrated that reliable variance of WISC-VCDN factor index scores was primarily due to the general factor, not the group factors. It was concluded that the cumulative weight of reliability and validity evidence suggests that psychologists should focus their interpretive efforts at the general factor level and exercise extreme caution when using group factor scores to make decisions about individuals.
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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 | 0.017 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".