Event Summary:
A one-day workshop organized by the Center for Interdisciplinary Research and
Consulting at the University of Maryland, Baltimore County (UMBC), and the
Center for Innovative Study Design (CISD) at Stanford University in the field of Clinical Trials and Regulatory Science.
Registration is now closed
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Organizing Committee:
Faculty from UMBC and Stanford University and leaders from FDA and industry.
For more information:
Please contact Dr. Yi Huang, Department of Mathematics and
Statistics, University of Maryland Baltimore County (UMBC),
1000 Hilltop Circle, Baltimore, MD 21250.
E-Mail: yihuang@umbc.edu.
For any Technical difficulties Please contact Zana Coulibaly at czana1@umbc.edu.
Participant Information
Xiaoyu Cai from The George Washington University.
Paper: Dilemma on Conditional Power Based Sample Size Re-estimation
Conditional power method was widely discussed in the literature on adaptive un-blinded sample size re-estimation (SSR) designs. The common application of conditional power method can be divided into three categories: (a) Futility assessment (b) Decision on sample size adjustment and (c) Decision on sample size increment. The conditional power based methods have advantages of controlling type I error rate and maintaining conditional power of the final test at a desired level. However, like most of other designs, it is not a universal optimal design, even among different approaches of adaptive designs. Moreover, the performance of conditional power method highly relies on some operational factors and sample distribution parameters such as the information fraction, the true treatment and so on. The problem is, except the basic statistical operating characteristics (type I error rate, power and so on), we have plenty of different criteria to compare different designs but hardly identify a most important criteria. For example, we may get better estimation of conditional power but lost efficiency under the same information fraction. Several problems may make it a dilemma whether or not it is worthwhile to use conditional power based adaptive design in the clinical trials. In this study, we will point out some of these potential problems.