Advanced Interpretation of the Neuropsychological Assessment Battery with Older Adults: Base Rate Analyses, Discrepancy Scores, and Interpreting Change
Bibliographic record
Abstract
The purpose of this study is to provide sophisticated psychometric information for advanced interpretation of the Neuropsychological Assessment Battery (NAB) with older adults. This information includes the base rates of low scores, intellectual-cognitive discrepancy scores, and a method for determining change. The NAB contains 24 co-normed neurocognitive tests across five domains (i.e., Attention, Language, Memory, Spatial, and Executive Functions); provides 36 primary T-scores, five domain indexes, and a total index score; and was co-normed with a measure of intellectual abilities (Reynolds Intellectual Assessment Scales; Reynolds Intellectual Screening Test [RIST]). Participants for this study were 742 older adults from the NAB standardization sample (mean age = 68.1, SD = 6.9). From the standardization sample, 42 older adults (mean age = 67.3 years, SD = 8.3) were administered the NAB two times (mean retest interval = 6.7 months, SD = 0.7). The base rates of low index scores and low primary scores are presented for the entire sample, as well as stratified by the level of intellectual abilities. RIST-NAB discrepancy scores are presented for the entire sample and for the different levels of intellectual abilities. Finally, information needed to interpret change in test performance on serial assessments is provided.
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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 | 0.048 | 0.158 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".