Weighted Statistics for Testing Multiple Endpoints in
Clinical Trials

Michael I Baron; Laurel M MacMillan

Research Article

Weighted Statistics for Testing Multiple Endpoints in Clinical Trials

Michael I Baron¹* and Laurel M MacMillan²

¹American University, Washington DC, USA

²Gryphon Scientific LLC, Takoma Park MD, USA

Corresponding Author

Received Date: April 05, 2019; Published Date: May 02, 2019

Abstract

Bonferroni, Holm, and Holm-type stepwise approaches have been well developed for the simultaneous testing of multiple hypotheses in medical experiments. Methods exist for controlling familywise error rates at their preset levels. This article shows how performance of these tests can often be substantially improved by accounting for the relative difficulty of tests. Introducing suitably chosen weights optimizes the error spending between the multiple endpoints. Such an extension of classical testing schemes generally results in a smaller required sample size without sacrificing the familywise error rate and power.

Keywords: Error spending; Familywise error rate; Likelihood ratio test; Minimax; Stepwise testing

Article Details

Citation

Michael I Baron, Laurel M MacMillan. Weighted Statistics for Testing Multiple Endpoints in Clinical Trials. Annal Biostat & Biomed Appli. 2(2): 2019. ABBA.MS.ID.000532.