Sample Size Estimation for Repeated Measures Analysis in Randomized Clinical Trials with Missing Data
In designing longitudinal studies, researchers must determine the number of subjects to randomize based on the power to detect a clinically meaningful treatment difference and a proposed analysis plan. In this paper, we present formulas for sample size estimation and an assessment of statistical power for a two-treatment repeated measures design allowing for subject attrition. These formulas can be used for comparing two treatment groups across time in terms of linear contrasts. Subjects are assumed to drop out of the study at random so that the missing data do not alter the parameters of interest.
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IJB publishes biostatistical models and methods, statistical theory, as well as original applications of statistical methods, for important practical problems arising from various sciences. It covers the entire range of biostatistics, from theoretical advances to relevant and sensible translations of a practical problem into a statistical framework, including advances in biostatistical computing.