Multivariate Models of Performance Validity: The Erdodi Index Captures the Dual Nature of Non-Credible Responding (Continuous and Categorical)
Why this work is in the frame
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Bibliographic record
Abstract
This study was designed to examine the classification accuracy of the Erdodi Index (EI-5), a novel method for aggregating validity indicators that takes into account both the number and extent of performance validity test (PVT) failures. Archival data were collected from a mixed clinical/forensic sample of 452 adults referred for neuropsychological assessment. The classification accuracy of the EI-5 was evaluated against established free-standing PVTs. The EI-5 achieved a good combination of sensitivity (.65) and specificity (.97), correctly classifying 92% of the sample. Its classification accuracy was comparable with that of another free-standing PVT. An indeterminate range between Pass and Fail emerged as a legitimate third outcome of performance validity assessment, indicating that the underlying construct is an inherently continuous variable. Results support the use of the EI model as a practical and psychometrically sound method of aggregating multiple embedded PVTs into a single-number summary of performance validity. Combining free-standing PVTs with the EI-5 resulted in a better separation between credible and non-credible profiles, demonstrating incremental validity. Findings are consistent with recent endorsements of a three-way outcome for PVTs ( Pass, Borderline, and Fail).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 it