Multiple pairwise comparison procedures based on the Lin and Wang test for right censored survival data

Abstract

When comparing the prognosis of more than two groups in clinical trials, researchers may use multiple comparison procedures to determine which treatments actually differ from one another. Methods of controlling the Family Wise Error (FWE) rate for multiple comparisons of survival curves have received attention in the statistical literature. Adjustments such as Bonferroni, Holm's, Steele's and the closed procedure based on the logrank test have been studied. If hazards cross, the adjustments based on the logrank test may not be the most appropriate. Chi (2005) developed multiple testing procedures based on weighted Kaplan–Meier statistics as these statistics may perform better than the logrank for non‐proportional hazards alternatives. The aim of this research is to propose multiple testing procedures based on the Lin and Wang (2004) statistic for all pairwise comparisons. Simulation studies have shown this statistic can be more powerful than the logrank for certain crossing hazards. Through simulation, the FWE rate and power of the Bonferroni and Holm's adjustments based on the Lin and Wang statistic will be studied. For comparison purposes, the same adjustment procedures based on the logrank and Wilcoxon will be included in the simulations. These methods are applied to data from the Bone marrow transplant registry.