Predictive Accuracy of the Wide Range Assessment of Memory and Learning in Children With Attention Deficit Hyperactivity Disorder and Reading Difficulties
Bibliographic record
Abstract
The predictive accuracy of the Wide Range Assessment of Memory and Learning (WRAML; Sheslow & Adams, 1990) over and above more standardized diagnostic tools in children with attention deficit hyperactivity disorder (ADHD) and reading disabilities (RD) was examined. Fifty-three children with ADHD, 63 with RD, 63 with ADHD-RD, and 112 normal comparison children were administered the WRAML, the Wechsler Intelligence Scale for Children-Third Edition (WISC-III; Wechsler, 1991), the Achenbach (1991) Child Behavior Checklist (CBCL), and the Woodcock-Johnson Psycho-Educational Battery-Revised (WJ-R; Woodcock & Johnson, 1989). Results of a series of discriminant function analyses revealed that the academic, intellectual, and behavioral measures could correctly classify 73.1% of children, but the WRAML subtests alone were able to correctly classify only 58.5% of participants. Combining all of the memory, academic, intellectual, and behavioral measures resulted in 77.5% of cases being correctly classified. These results suggest that the use of a measure of memory functioning such as the WRAML did not significantly improve the predictive accuracy of a diagnosis of ADHD, RD, or both over and above more standard diagnostic academic, intellectual, and behavioral measures.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".