Statistical Methods in the Design and Analysis of Clinical Trials and Assessment of Prediction with Patient-Specific Information

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In the next five years, I will develop new methods in estimation, testing and making statistical inference for the accuracy of prediction models built upon patient specific data. Prediction error will be studied for survival outcome data with various types of censoring, for cure-rate models which accommodate cured and uncured patient populations and for high dimensional data. The research is important for health and medical researchers who are making predictions for patients' prognostics, disease categories or responses to therapy. It is also an important area of methodological research in statistics in need of computational methods and theoretical development. I will train a Ph.D. student in dealing with these statistical challenges to build up the research in this area for both practical use and advancement of statistical science.