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Activity Number: 339
Type: Topic Contributed
Date/Time: Tuesday, August 6, 2013 : 10:30 AM to 12:20 PM
Sponsor: Biopharmaceutical Section
Abstract - #307900
Title: Information-Based Sample Size Re-Estimation for Longitudinal Trials
Author(s): Jing Zhou*+ and Yue Shentu and Jiajun Liu and Keaven Anderson
Companies: UNC-Chapel Hill and Merck and Regeneron Pharmaceuticals, Inc. and Merck Research Laboratories
Keywords: Sample size re-estimation ; Information ; Group sequential design ; Longitudinal data analysis

Group sequential design has become more popular in clinical trials since it allows for trials to stop early for futility or efficacy to save time and resources. However, this approach is less well-known for longitudinal analysis. To develop a method aiming to perform longitudinal trials with group sequential design, the most pressing concern is whether we can maintain the power and type-I error, especially when some assumptions used in the initial sample size calculation are incorrect. Hence we propose a sample size re-estimation method based on information or variance. Updating the sample size at each interim analysis will allow us to maintain the target power while controlling the type-I error rate. We will illustrate our strategy by real data analysis examples and simulations and compare the results with those obtained using fixed design and group-sequential design without sample size re-estimation.

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