Diagnostic Test Score Validation With a Fallible Criterion

Abstract

Criterion-related validation of diagnostic test scores for a construct of interest is complicated by the unavailability of the construct directly. The standard method, Known Group Validation, assumes an infallible reference test in place of the construct, but infallible reference tests are rare. In contrast, Mixed Group Validation allows for a fallible reference test, but has been found to make strong assumptions not appropriate for the majority of diagnostic test validation studies. The Neighborhood model is adapted for the purpose of diagnostic test validation, which makes alternate, but also strong, assumptions. The statistical properties of the Neighborhood model are evaluated and the assumptions are reviewed in the context of diagnostic test validation. Alternatively, strong assumptions may be avoided by estimating only intervals for the validity estimates, instead of point estimates. The Method of Bounds is also adapted for the purpose of diagnostic test validation, and an extension, Method of Bounds–Test Validation, is introduced here for the first time. All three point-estimate methods were found to make strong assumptions concerning the conditional relationships between the tests and the construct of interest, and all three lack robustness to assumption violation. The Method of Bounds–Test Validation was found to perform well across a range of plausible simulated datasets where the point-estimate methods failed. The point-estimate methods are recommended in special cases where the assumptions can be justified, while the interval methods are appropriate more generally.