Survival Analysis

Survival analysis is the branch of statistics that deals with analyzing data when the outcome of interest is time to some event, such as death or disease progression. Such outcomes are commonly only partially observed due to participants dropping out of the study or not having experienced the event of interest at the end of study (referred to as censoring). Dr. Steingrimsson works on developing adaptations of machine learning algorithm that can handle the complications arising from time-to-event outcomes. Dr. Chrysanthopoulou works on statistical approaches for predicting time-to-event data, with applications to complex predictive models (e.g., microsimulation models) used in Medical Decision Making and Comparative Effectiveness Research. In addition, several faculty members are involved in interdisciplinary collaborations that involve analysis of time-to-event outcomes. 

Stavroula Chrysanthopoulou
BACK TO THEORY AND METHODS

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