Matching in studies of classification accuracy: implications for analysis, efficiency, and assessment of incremental value.
In case-control studies evaluating the classification accuracy of a marker, controls are often matched to cases with respect to factors associated with the marker and disease status. In contrast with matching in epidemiologic etiology studies, matching in the classification setting has not been rigorously studied. In this article, we consider the implications of matching in terms of the choice of statistical analysis, efficiency, and assessment of the incremental value of the marker over the matching covariates. We find that adjustment for the matching covariates is essential, as unadjusted summaries of classification accuracy can be biased. In many settings, matching is the most efficient covariate-dependent sampling scheme, and we provide an expression for the optimal matching ratio. However, we also show that matching greatly complicates estimation of the incremental value of the marker. We recommend that matching be carefully considered in the context of these findings.
Janes
Holly
H
Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St., Baltimore, MD 21205, USA. hjanes@jhsph.edu
Pepe
Margaret S
MS
D000465:Algorithms; D016022:Case-Control Studies; D003627:Data Interpretation, Statistical; D017720:Molecular Epidemiology / Q000379:methods*; D012372:ROC Curve; D015203:Reproducibility of Results; D018401:Sample Size; D012680:Sensitivity and Specificity