Family-Wise Error Rate Controlling Procedures for Discrete Data

Document Type

Article

Publication Date

1-2-2020

Abstract

In applications such as clinical safety analysis, the data of the experiments usually consist of frequency counts. In the analysis of such data, researchers often face the problem of multiple testing based on discrete test statistics, aimed at controlling family-wise error rate (FWER). Most existing FWER controlling procedures are developed for continuous data, which are often conservative when analyzing discrete data. By using minimal attainable p-values, several FWER controlling procedures have been specifically developed for discrete data in the literature. In this article, by using known marginal distributions of true null p-values, three more powerful stepwise procedures are developed, which are modified versions of the conventional Bonferroni, Holm and Hochberg procedures, respectively. It is shown that the first two procedures strongly control the FWER under arbitrary dependence and are more powerful than the existing Tarone-type procedures, while the last one only ensures control of the FWER in special settings. Through extensive simulation studies, we provide numerical evidence of superior performance of the proposed procedures in terms of the FWER control and minimal power. A real clinical safety data are used to demonstrate applications of our proposed procedures. An R package “MHTdiscrete” and a web application are developed for implementing the proposed procedures.

Identifier

85073824488 (Scopus)

Publication Title

Statistics in Biopharmaceutical Research

External Full Text Location

https://doi.org/10.1080/19466315.2019.1654912

e-ISSN

19466315

First Page

117

Last Page

128

Issue

1

Volume

12

Grant

DMS-1309162

Fund Ref

National Science Foundation

This document is currently not available here.

Share

COinS