Mei-Cheng Wang

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Survival Analysis  (Biostatistics 140.641) — offered every year

This intermediate-level course introduces fundamental concepts, theory and methods in survival analysis. The course emphasizes statistical tools and model interpretations which are useful in medical follow-up studies and in general time-to-event studies. The content includes hazard functions, survival functions, types of censoring and truncation, Kaplan-Meier estimates, log-rank tests and their generalization. Parametric models and inference include likelihood estimation and the exponential, Weibull, log-logistic and other relevant distributions. Statistical methods and theory for the proportional hazard model (Cox model) are discussed  in detail with extensions to time-dependent covariates. Clinical and epidemiological examples (through class presentations) will be discussed and illustrated with various statistical procedures in class and also through homework assignments.

 

 

Advanced Survival Analysis  (Biostatistics 140.741) — offered every other year



This advanced course introduces statistical models and methods useful for analyzing univariate and multivariate failure time data. It extends the course of Survival Analysis (Biostatistics 140.641) to topics on semi-transformation model, competing risks models, length-bias and prevalent samplings, multivariate and frailty survival models, models and methods for analyzing recurrent events data, and martingale theory for counting processes. Emphases are placed on nonparametric and semiparametric approaches for modeling, estimation and inferential results. Clinical and epidemiological examples are presented in class to illustrate statistical procedures.

 

 

New Course To Be Offered in 2018:  Biomarkers, Risk Prediction and Precision Medicine — offered every other year

 

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