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Abstract:
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Testing statistical hypothesis is usually done in sciences using p-values. Recently, e-values have gained attention as potential alternatives to p-values as measures of uncertainty, significance and evidence. We discuss some advantages and disadvantages of e-values versus p-values in multiple hypothesis testing. Statistical procedures based on e-values enjoy many attractive properties. In particular, we design a natural analog of the Benjamini-Hochberg (BH) procedure for false discovery rate (FDR) control that utilizes e-values (e-BH) and compare it with the standard procedure for p-values. Unlike the usual BH procedure, the e-BH procedure controls the FDR at the desired level for any dependence structure between the e-values.
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