A Permutation Test For Comparing Predictive Values In Clinical Trials

Screening tests or diagnostic tests are important for early detection and treatment of disease. There are four well-known measurements, sensitivity (SE), specificity (SP), positive predictive value (PPV) and negative predictive value (NPV) in diagnostic studies. For comparing SEs/SPs, McNemar test is widely used, but there are only few methods for the comparison of PPVs/NPVs. Moreover, all of these methods are based on large-sample theory.

So, in this talk, firstly, we investigate the performance of those methods when the sample size is small. In addition, we propose a permutation test for comparing two PPVs/NPVs we can apply even if the sample size is small. Finally, we show the performance of the proposed method with some existing methods via simulation studies.