Power and sample size calculation for paired right-censored data based on survival copula models. Issue 6 (3rd July 2018)

• Record Type: Journal Article
• Authors: Su, Pei-Fang; Chang, Sheng-Mao
• Is Part Of: Communications in statistics. Volume 47:Issue 6(2018)
• Page Start: 1565
• Page End: 1582
• Publication Date: 2018-07-03
• Subjects: Kaplan–Meier statistic -- Logrank test -- Survival copula -- Weibull marginal; 62N02; Mathematical statistics -- Periodicals; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5
• DOI: 10.1080/03610918.2017.1300264
• Languages: English
• ISSNs: 0361-0918

Abstract

Abstract: Sample size determination is essential during the planning phases of clinical trials. To calculate the required sample size for paired right-censored data, the structure of the within-paired correlations needs to be pre-specified. In this article, we consider using popular parametric copula models, including the Clayton, Gumbel, or Frank families, to model the distribution of joint survival times. Under each copula model, we derive a sample size formula based on the testing framework for rank-based tests and non-rank-based tests (i.e., logrank test and Kaplan–Meier statistic, respectively). We also investigate how the power or the sample size was affected by the choice of testing methods and copula model under different alternative hypotheses. In addition to this, we examine the impacts of paired-correlations, accrual times, follow-up times, and the loss to follow-up rates on sample size estimation. Finally, two real-world studies are used to illustrate our method and R code is available to the user.