Sample size and power determination in joint modeling of longitudinal and survival data.

ABSTRACT: Owing to the rapid development of biomarkers in clinical trials, joint modeling of longitudinal and survival data has gained its popularity in the recent years because it reduces bias and provides improvements of efficiency in the assessment of treatment effects and other prognostic factors. Although much effort has been put into inferential methods in joint modeling, such as estimation and hypothesis testing, design aspects have not been formally considered. Statistical design, such as sample size and power calculations, is a crucial first step in clinical trials. In this paper, we derive a closed-form sample size formula for estimating the effect of the longitudinal process in joint modeling, and extend Schoenfeld's sample size formula to the joint modeling setting for estimating the ove

SUBMITTER: Chen LM 

PROVIDER: S-EPMC3278672 | biostudies-literature | 2011 Aug

REPOSITORIES: biostudies-literature