| Literature DB >> 21391001 |
Abstract
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.Entities:
Mesh:
Year: 2011 PMID: 21391001 PMCID: PMC3157149 DOI: 10.1080/10543406.2011.550109
Source DB: PubMed Journal: J Biopharm Stat ISSN: 1054-3406 Impact factor: 1.051