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
⇒View Archives here⇐
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
Ao Yuan from Georgetown University.
Paper: Nonparametric test for the evaluation of group sequential clinical trial with covariate information
Group sequential design is frequently used in clinical trials to evaluate a new treatment vs a control. Although nonparametric methods have the advantage of robustness, most existing such methods do not take into consideration of covariate information, which is can be used to improve the test accuracy if incorporated properly. We address this problem using a two-sample U-statistic that incorporates covariate information into the test statistic. Asymptotic properties of the proposed estimator are presented. Simulations are conducted to evaluate its performances. We then apply the proposed method in the analysis of a Parkinson disease clinical trial data, and demonstrate that the significant treatment effect from deprenyl could be detected at an early stage.