B-01 * Comparing the Canadian and American WAIS-IV Normative Systems in a Clinical Population
Bibliographic record
Abstract
Objective: Clinical observations of large discrepancies in individual intelligence quotient (IQ) scores calculated using Canadian vs. American norms for the WAIS-IV have raised questions about the appropriateness of the Canadian normative system for use with a clinical population in Canada. The purpose of this study was to compare the interpretive effects of applying the American and Canadian normative systems in a clinical sample. Method: We analyzed archival data from 338 Canadian individuals who received routine neuropsychological assessment between 2008 and 2010. Differences between Canadian and American standard scores for the Wechsler Adult Intelligence Scale–IV (WAIS-IV) data were determined using a Multivariate Analysis of Variance (MANOVA) and three mixed model Analyses of Variance (ANOVAs) were used to further assess the pattern of differences across Canadian and American normed standardized scores. Results: Full Scale IQ (FSIQ) and index scores calculated using the Canadian normative system were systematically lower than those calculated using the American system. The largest differences in FSIQ were obtained for individuals classified as having Extremely Low or Borderline intellectual functioning, and for individuals below the age of 45. In our sample, the choice to use the Canadian rather than the American normative system resulted in clinically different classification of greater impairment in intellectual ability for 52.8% of individual patients. Conclusion(s): Our findings underscore the need for caution when choosing a normative system with which to interpret results of the WAIS-IV in the context of a neuropsychological test battery in Canada.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".