Interval estimation for drop-the-losers designs

• 成果类型: Article
• 署名作者: Wu, Samuel S.; Wang, Weizhen; Yang, Mark C. K.
• 署名单位: State University System of Florida; University of Florida; University System of Ohio; Wright State University Dayton; State University System of Florida; University of Florida
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/asq003
• 发表日期: 2010
• 页码: 405418
• 关键词: clinical-trials; adaptive design; selection

摘要

In the first stage of a two-stage, drop-the-losers design, a candidate for the best treatment is selected. At the second stage, additional observations are collected to decide whether the candidate is actually better than the control. The design also allows the investigator to stop the trial for ethical reasons at the end of the first stage if there is already strong evidence of futility or superiority. Two types of tests have recently been developed, one based on the combined means and the other based on the combined p-values, but corresponding interval estimators are unavailable except in special cases. The problem is that, in most cases, the interval estimators depend on the mean configuration of all treatments in the first stage, which is unknown. In this paper, we prove a basic stochastic ordering lemma that enables us to bridge the gap between hypothesis testing and interval estimation. The proposed confidence intervals achieve the nominal confidence level in certain special cases. Simulations show that decisions based on our intervals are usually more powerful than those based on existing methods.