Sample size calculations for group randomized trials with unequal group sizes through Monte Carlo simulations

Yang Shi, Ji Hyun Lee

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Group randomized trial design is common in cancer prevention and health promotion research with intervention development. Several methods have been developed to handle the design and analytical issues for group randomized trial including the intraclass correlation coefficient. The widely used methods for the sample size calculation for the group randomized trial assume equal sizes across groups. In practice this assumption often fails and group randomized trial studies suffer from considerably lower statistical power than as planned. A few studies have developed sample size calculation methods for unequal group sizes, but most of them are limited to continuous outcomes. In this study, we develop a method for sample size calculation for group randomized trial studies with unequal group sizes based on Monte Carlo simulation in the mixed effect model framework. This approach incorporates the variation of group sizes and can be applied to group randomized trials with different types of outcomes. Further, it is easy to implement and can be applied to most commonly used group randomized trial designs such as pre-and-post cross-sectional and cohort study designs. We demonstrate the application of the proposed approach to two-arm group randomized trial studies with continuous and binary outcomes through simulations and analysis of a real group randomized trial dataset.

Original languageEnglish (US)
Pages (from-to)2569-2580
Number of pages12
JournalStatistical Methods in Medical Research
Volume27
Issue number9
DOIs
Publication statusPublished - Sep 1 2018

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Keywords

  • Monte Carlo simulation
  • Sample size calculation
  • group randomized trials
  • mixed effects model
  • unequal group size

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability
  • Health Information Management

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