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Updated: Oct 23, 2025

Cross-Modal Multivariate Pattern Analysis
Published on: November 9, 2011
Five shades of gray: Conceptual and methodological issues around multivariate models of performance validity
Objective:
This study was designed to empirically investigate the signal detection profile of various multivariate models of performance validity tests (MV-PVTs) and explore several contested assumptions underlying validity assessment in general and MV-PVTs specifically.
Method:
Archival data were collected from 167 patients (52.4%male; MAge = 39.7) clinicially evaluated subsequent to a TBI. Performance validity was psychometrically defined using two free-standing PVTs and five composite measures, each based on five embedded PVTs.
Results:
MV-PVTs had superior classification accuracy compared to univariate cutoffs. The similarity between predictor and criterion PVTs influenced signal detection profiles. False positive rates (FPR) in MV-PVTs can be effectively controlled using more stringent multivariate cutoffs. In addition to Pass and Fail, Borderline is a legitimate third outcome of performance validity assessment. Failing memory-based PVTs was associated with elevated self-reported psychiatric symptoms.
Conclusions:
Concerns about elevated FPR in MV-PVTs are unsubstantiated. In fact, MV-PVTs are psychometrically superior to individual components. Instrumentation artifacts are endemic to PVTs, and represent both a threat and an opportunity during the interpretation of a given neurocognitive profile. There is no such thing as too much information in performance validity assessment. Psychometric issues should be evaluated based on empirical, not theoretical models. As the number/severity of embedded PVT failures accumulates, assessors must consider the possibility of non-credible presentation and its clinical implications to neurorehabilitation.
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