title: Sample size reestimation by Bayesian prediction.
abstract: We review a Bayesian predictive approach for interim data monitoring and propose its application to interim sample size reestimation for clinical trials. Based on interim data, this approach predicts how the sample size of a clinical trial needs to be adjusted so as to claim a success at the conclusion of the trial with an expected probability. The method is compared with predictive power and conditional power approaches using clinical trial data. Advantages of this approach over the others are discussed.
authors.affiliation: Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA. wang_ming-dauh@lilly.com
authors.forename: Ming-Dauh
authors.initials: MD
authors.lastname: Wang
mesh_terms: D001499:Bayes Theorem; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D017322:Clinical Trials, Phase II as Topic / Q000706:statistics & numerical data; D003627:Data Interpretation, Statistical; D018401:Sample Size