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01, 2022;28 (1): 40-67.

Sample size calculation for clustered survival data under subunit randomization.

Jianghao Li, Sin-Ho Jung
Author Information
  1. Jianghao Li: Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, 27705, USA.
  2. Sin-Ho Jung: Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, 27705, USA. sinho.jung@duke.edu. ORCID
PMID: 34716530 DOI: 10.1007/s10985-021-09538-0

Abstract

Each cluster consists of multiple subunits from which outcome data are collected. In a subunit randomization trial, subunits are randomized into different intervention arms. Observations from subunits within each cluster tend to be positively correlated due to the shared common frailties, so that the outcome data from a subunit randomization trial have dependency between arms as well as within each arm. For subunit randomization trials with a survival endpoint, few methods have been proposed for sample size calculation showing the clear relationship between the joint survival distribution between subunits and the sample size, especially when the number of subunits from each cluster is variable. In this paper, we propose a closed form sample size formula for weighted rank test to compare the marginal survival distributions between intervention arms under subunit randomization, possibly with variable number of subunits among clusters. We conduct extensive simulations to evaluate the performance of our formula under various design settings, and demonstrate our sample size calculation method with some real clinical trials.

Keywords

Censoring Design effect Intracluster correlation coefficient Variable cluster size Weighted rank test

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MeSH Term

Cluster Analysis
Humans
Random Allocation
Research Design
Sample Size
Journal Article

Word Cloud

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