Comparison of proportions for composite endpoints with missing components

Composite endpoints are commonly used in clinical trials. When there are missing values in their individual components, inappropriate handling of the missingness may create inefficient or even biased estimates of the proportions of successes in composite endpoints. Assuming missingness is completely at random or dependent on baseline covariates, we derived a maximum likelihood estimator of the proportion of successes in a three-component composite endpoint and closed-form variance for the proportion, and compared two groups in the difference in proportions and in the logarithm of a relative risk. Sample size and statistical power were studied. Simulation studies were used to evaluate the performance of the developed methods. With a moderate sample size the developed methods works satisfactorily.