Investigating the Factor Structure of the Preclinical Alzheimer Cognitive Composite and Cognitive Function Index across Racial/Ethnic, Sex, and Aβ Status Groups in the A4 Study
Bibliographic record
Abstract
BACKGROUND: Disparities in Alzheimer's disease (AD) are well-documented among different racial/ethnic groups and between sex/genders. Neuropsychological assessment provides important information about cognitive changes and can offer valuable insights into disparities. However, neuropsychological measures must be comparable across racial/ethnic and sex/gender groups to accurately interpret disparities. OBJECTIVES: To evaluate measurement invariance (equivalence) of the Preclinical Alzheimer Cognitive Composite (PACC) and the Cognitive Function Index across racial/ethnic, sex/gender, and β-amyloid (Aβ) status groups. DESIGN, SETTING, PARTICIPANTS: Cross-sectional analysis of screening data from the Anti-Amyloid in Asymptomatic AD (A4) Study. The study enrolled participants aged 65-85 from sites across the United States, Canada, Australia, and Japan. MEASUREMENTS: Participants completed the PACC and the Cognitive Function Index. Participants classified as cognitively normal also underwent a Positron Emission Tomography (PET) scan to determine Aβ status. RESULTS: Participants self-identified as non-Hispanic White (n=5241), non-Hispanic Black (n=267), Asian (n=228), or Hispanic White (n=225) as well as male (n=2885) or female (n=3076). Among those who underwent a PET scan, 3115 were classified as Aβ- and 1309 were classified as Aβ+. We found support for a one-factor model for both the PACC and Cognitive Function Index across the full sample and in samples stratified by race/ethnicity, sex/gender, and Aβ status. The one-factor model of the PACC and Cognitive Function Index demonstrated scalar measurement invariance across racial/ethnic, sex/gender, and Aβ status groups. CONCLUSIONS: Our findings suggest that performance on the PACC and Cognitive Function Index can be compared across the racial/ethnic, sex/gender, and Aβ status groups examined in this study.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".