Longitudinal and Sex Measurement Invariance of the Affective Neuroscience Personality Scales
Bibliographic record
Abstract
The Affective Neuroscience Personality Scales (ANPS) is a personality instrument based on six evolutionary-related brain systems that are at the foundation of human emotions and behaviors: SEEKING, CARING, PLAYFULNESS, FEAR, ANGER, and SADNESS. We sought to assess for the short and long versions of the ANPS: (a) the longitudinal measurement invariance and long-term (4-year) stability and (b) the sex measurement invariance. Using data from a Canadian cohort ( N = 518), we used single-group confirmatory factor analysis to assess longitudinal invariance and multiple-group confirmatory factor analysis to assess sex invariance, according to a five-step approach evaluating five invariance levels (configural, metric, scalar, residual, and complete). Results supported full longitudinal invariance for both versions for all invariance levels. Partial residual invariance was supported for sex invariance. The long-term stability of both versions was good to excellent. Implications for personality assessment and ANPS development are discussed.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".