Affinity-Based Measures of Diagnostic Test Accuracy

Miguel de Carvalho (University of Edinburgh)

Friday 28th April, 2017 15:00-16:00 Sir Alexander Stone, room 204

Abstract

We propose new summary measures of diagnostic test accuracy which can be used as companions, or possibly as alternatives, to existing diagnostic accuracy measures. Conceptually, our summary measures are tantamount to the so-called Hellinger affinity and we show that they can be regarded as measures of agreement constructed from similar geometrical principles as Pearson correlation. A covariate-adjusted version of our summary index is developed, which can be used to assess the discrimination performance of a diagnostic test, conditionally on the value of a predictor. Nonparametric Bayes estimators for the proposed indexes are devised, theoretical properties of the corresponding priors are derived, and the performance of our methods is assessed through a simulation study. Data from a prostate cancer diagnosis study are used to illustrate our methods. Joint work with G. Page and B. Barney (Brigham Young University).

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