Harmonized Cognitive Assessment Protocol in the English Longitudinal Study of Ageing: Contrasting approaches to evaluation of factor structure
Bibliographic record
Abstract
OBJECTIVES: Cognitive theories and previous research on cognitive performance suggest a hierarchical pattern of interrelationships among cognitive tests, but the psychometric properties of the same tests may change when adapted for a different context or applied to a different population. We evaluated the factor structure of a cognitive battery of tests using an exploratory, data-driven approach and a confirmatory, theory-driven approach. DESIGN: We estimated exploratory factor analyses (EFA) and confirmatory factor analysis (CFA). Agreement between the results based on the EFA and CFA approaches was evaluated by contrasting the identified domains and their corresponding items. SETTING: Epidemiologic cohort study in England. PARTICIPANTS: Adults aged 65+ in the English Longitudinal Study of Ageing (ELSA). MEASUREMENTS: Harmonized Cognitive Assessment Protocol battery of cognitive tests, adapted for the English context. RESULTS: Both the EFA and CFA solutions yielded adequate model fit (RMSEA's < 0.05; CFI's > 0.92; SRMR's<0.06). However, only after multiple iterative steps, the EFA produced a factor structure that largely conformed to a priori theory of human cognitive abilities. CONCLUSIONS: This study provides an important cautionary tale for factor analytic approaches to evaluating domain structures when the tests available for factor analysis do not encompass a broad enough content of the construct: a factor solution is only as good as the bank of available items.
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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 | 0.138 | 0.180 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".