Thursday, November 8, 2018 - 2:30pm - 3:00pm
Feifang Hu (George Washington University)
Covariate-adjusted randomization procedure is frequently used in comparative studies (such as clinical trials for precision medicine) to increase the covariate balance across treatment groups. However, as the randomization inevitably uses the covariate information when forming balanced treatment groups, the validity of classical statistical methods following such randomization is often unclear.In this talk, we discuss the theoretical properties of statistical methods based on general covariate-adjusted randomization under the linear model framework.
Thursday, September 14, 2017 - 3:30pm - 4:00pm
Feifang Hu (George Washington University)
Precision medicine is the systematic use of information pertaining to an individual patient to select or optimize the patient’s preventative and therapeutic care. In recent literature, biomarkers have been classified to predictive biomarkers and prognostic biomarkers based one their role in clinical studies. To design a clinical trial for precision medicine, one should include both predictive and prognostic biomarkers. In this talk, we will propose a new family of covariate-adjusted response-adaptive designs, which incorporate these biomarkers as well as the responses.
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