Validity and Power Considerations on Hypothesis Testing Under Minimization

• Activity Number: 659
• Type: Contributed
• Date/Time: Thursday, August 13, 2015 : 8:30 AM to 10:20 AM
• Sponsor: Biopharmaceutical Section
• Author(s): Zhenzhen Xu* and Michael Proschan and Shiowjen Lee
• Companies: FDA and NIH/NIAID and FDA
• Keywords: Covariate adaptive randomization ; Minimization ; Dynamic allocation ; Re-randomization test ; Temporal trend ; Validity

Abstract

Minimization, a dynamic allocation method, is gaining popularity, especially in cancer clinical trials. Aiming to achieve balance on all important prognostic factors simultaneously, this procedure can lead to a substantial reduction in covariate imbalance compared to conventional randomization in small clinical trials. While minimization has generated enthusiasm, some controversy exists over the proper analysis of such a trial. Critics argue that standard testing methods that do not account for the dynamic allocation algorithm can lead to invalid statistical inference. Acknowledging this limitation, the ICH E9 Guideline suggests that ``The complexity of the logistics and potential impact on analyses be carefully evaluated when considering dynamic allocation.'' In this article, we investigate the proper analysis approaches to inference in a minimization design for both continuous and time-to-event endpoints, and evaluate the validity and power of these approaches under a variety of scenarios both theoretically and empirically.