Aggregating validity indicators: The salience of domain specificity and the indeterminate range in multivariate models of performance validity assessment

This study was designed to examine the domain specificity hypothesis in performance validity tests (PVTs) and the epistemological status of an indeterminate range when evaluating the credibility of a neuropsychological profile using a multivariate model of performance validity assessment. While previous research suggests that aggregating PVTs produces superior classification accuracy compared to individual instruments, the effect of the congruence between the criterion and predictor variable on signal detection and the issue of classifying borderline cases remain understudied. Data from a mixed clinical sample of 234 adults referred for cognitive evaluation (M-Age = 46.6; M-Education = 13.5) were collected. Two validity composites were created: one based on five verbal PVTs (EI-5(VER)) and one based on five nonverbal PVTs (EI-5(NV)) and compared against several other PVTs. Overall, language-based tests of cognitive ability were more sensitive to elevations on the EI-5(VER) compared to visual-perceptual tests; whereas, the opposite was observed with the EI-5(NV). However, the match between predictor and criterion variable had a more complex relationship with classification accuracy, suggesting the confluence of multiple factors (sensory modality, cognitive domain, testing paradigm). An indeterminate range of performance validity emerged that was distinctly different from both the Pass and the Fail group. Trichotomized criterion PVTs (Pass-Borderline-Fail) had a negative linear relationship with performance on tests of cognitive ability, providing further support for an in-between category separating the unequivocal Pass and unequivocal Fail classification range. The choice of criterion variable can influence classification accuracy in PVT research. Establishing a Borderline range between Pass and Fail more accurately reflected the distribution of scores on multiple PVTs. The traditional binary classification system imposes an artificial dichotomy on PVTs that was not fully supported by the data. Accepting indeterminate as a legitimate third outcome of performance validity assessment has the potential to improve the clinical utility of PVTs and defuse debates regarding near-Passes and soft Fails.