Information-based sample size re-estimation in group sequential design for longitudinal trials
| Autor: | Keaven M. Anderson, Adeniyi J. Adewale, Jing Zhou, Yue Shentu, Jiajun Liu |
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| Rok vydání: | 2014 |
| Předmět: |
Statistics and Probability
Estimation Clinical Trials as Topic Sequential estimation Models Statistical Early stopping Epidemiology Computer science Variance (accounting) Interim analysis Clinical trial Research Design Sample size determination Sample Size Statistics Humans Computer Simulation Longitudinal Studies Type I and type II errors |
| Zdroj: | Statistics in Medicine. 33:3801-3814 |
| ISSN: | 0277-6715 |
| Popis: | Group sequential design has become more popular in clinical trials because 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. We have observed repeated cases of studies with longitudinal data where there is an interest in early stopping for a lack of treatment effect or in adapting sample size to correct for inappropriate variance assumptions. We propose an information-based group sequential design as a method to deal with both of these issues. Updating the sample size at each interim analysis makes it possible to maintain the target power while controlling the type I error rate. We will illustrate our strategy with examples and simulations and compare the results with those obtained using fixed design and group sequential design without sample size re-estimation. Copyright © 2014 John Wiley & Sons, Ltd. |
| Databáze: | OpenAIRE |
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