Assessing Underreporting Response Bias on the MMPI-2
Bibliographic record
Abstract
The authors assess the replicability of the two-factor model of underreporting response style. They then examine the relative performance of scales measuring these styles in analog (ARD) and differential prevalence group (DPG) designs. Principal components analysis produced a two-factor structure corresponding to self-deceptive (SD) and impression management (IM) response styles. The IM factor scale and related individual validity scales were elevated among research participants instructed to fake good on the MMPI-2 as compared with participants who completed the MMPI-2 under standard instructions (ARD) and among individuals evaluated in real-life assessment contexts where underreporting is expected (DPG). Participants in DPG samples produced significantly higher SD factor and related individual scale scores than did the ARD participants instructed to fake good. These findings confirm that the MMPI-2 validity scales measure two types of underreporting styles and that these styles may operate differently in ARD versus DPG designs.
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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 | 0.029 | 0.133 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".