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Abstract:
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Continuing technological advancements allow researchers and clinicians to measure an increasingly vast diversity of clinical and biological markers, rapidly increasing our understanding of disease processes. The wide range of newly available markers holds great potential for the personalization of medical care through accurate prediction of outcomes in individual patients. Traditional statistical methods for using patient's marker values to make personalized predictions are derived under a strong assumption that the true model relating markers to the response can be identified, at least with a large enough sample. In practice, however, it is difficult if not impossible even to locate a class of models containing the truth. In this talk, we will discuss various methods for model estimation, evaluation, and comparison for predicting future outcomes.
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