Robust covariate-adjusted log-rank statistics and corresponding sample size formula for recurrent events data.

ABSTRACT: Recurrent events data are frequently encountered in clinical trials. This article develops robust covariate-adjusted log-rank statistics applied to recurrent events data with arbitrary numbers of events under independent censoring and the corresponding sample size formula. The proposed log-rank tests are robust with respect to different data-generating processes and are adjusted for predictive covariates. It reduces to the Kong and Slud (1997, Biometrika 84, 847-862) setting in the case of a single event. The sample size formula is derived based on the asymptotic normality of the covariate-adjusted log-rank statistics under certain local alternatives and a working model for baseline covariates in the recurrent event data context. When the effect size is small and the baseline covariates do

SUBMITTER: Song R 

PROVIDER: S-EPMC2795392 | biostudies-literature | 2008 Sep

REPOSITORIES: biostudies-literature