Model-Based Person Fit Statistics Applied to the Wechsler Adult Intelligence Scale IV

An important task in clinical neuropsychology is to evaluate whether scores obtained on a test battery, such as the Wechsler Adult Intelligence Scale Fourth Edition (WAIS-IV), can be considered "credible" or "valid" for a particular patient. Such evaluations are typically made based on responses to performance validity tests (PVTs). As a complement to PVTs, we propose that WAIS-IV profiles also be evaluated using a residual-based M-distance ( $d_{\mathrm{ri}}^2$ ) person fit statistic. Large $d_{\mathrm{ri}}^2$ values flag profiles that are inconsistent with the factor analytic model underlying the interpretation of test scores. We first established a well-fitting model with four correlated factors for 10 core WAIS-IV subtests derived from the standardization sample. Based on this model, we then performed a Monte Carlo simulation to evaluate whether a hypothesized sampling distribution for $d_{\mathrm{ri}}^2$ was accurate and whether $d_{\mathrm{ri}}^2$ was computable, under different degrees of missing subtest scores. We found that when the number of subtests administered was less than 8, $d_{\mathrm{ri}}^2$ could not be computed around 25% of the time. When computable, $d_{\mathrm{ri}}^2$ conformed to a ${\chi }^2$ distribution with degrees of freedom equal to the number of tests minus the number of factors. Demonstration of the $d_{\mathrm{ri}}^2$ index in a large sample of clinical cases was also provided. Findings highlight the potential utility of the $d_{\mathrm{ri}}^2$ index as an adjunct to PVTs, offering clinicians an additional method to evaluate WAIS-IV test profiles and improve the accuracy of neuropsychological evaluations.