Medical researchers endeavor to identify potentially useful biomarkers to develop marker-based screening assays for disease diagnosis and prevention. Useful summary measures which properly evaluate the discriminative ability of diagnostic markers are critical for this purpose. Literature and existing software, for example, R packages nicely cover summary measures for diagnostic markers used for the binary case (e.g., healthy vs. diseased). An intermediate population at an early disease stage usually exists between the healthy and the fully diseased population in many disease processes. Supporting utilities for three-group diagnostic tests are highly desired and important for identifying patients at the early disease stage for timely treatments. However, application packages which provide summary measures for three ordinal groups are currently lacking. This paper focuses on two summary measures of diagnostic accuracy-volume under the receiver operating characteristic surface and the extended Youden index, with three diagnostic groups. We provide the R package DiagTest3Grp to estimate, under both parametric and nonparametric assumptions, the two summary measures and the associated variances, as well as the optimal cut-points for disease diagnosis. An omnibus test for multiple markers and a Wald test for two markers, on independent or paired samples, are incorporated to compare diagnostic accuracy across biomarkers. Sample size calculation under the normality assumption can be performed in the R package to design future diagnostic studies. A real world application evaluating the diagnostic accuracy of neuropsychological markers for Alzheimer's disease is used to guide readers through step-by-step implementation of DiagTest3Grp to demonstrate its utility.
Keywords: DiagTest3Grp; R; Youden index; diagnostic test; three ordinal groups; volume under the ROC surface.