Bayesian Sample Size Determination for a Clinical Trial with Correlated Continuous and Binary Outcomes

Abstract

In clinical trials, multiple outcomes are often collected in order to simultaneously assess effectiveness and safety. We develop a Bayesian procedure for determining the required sample size in a regression model where a continuous efficacy variable and a binary safety variable are observed. The sample size determination procedure is simulation based. The model accounts for correlation between the two variables. Through examples we demonstrate that savings in total sample size are possible when the correlation between these two variables is sufficiently high.