Johns Hopkins University 3 credits Biostatistics
Introduces fundamental concepts, theory and methods in survival analysis. Emphasizes statistical tools and model interpretations which are useful in medical follow-up studies and in general time-to-event studies. Includes hazard function, survival function, different types of censoring, Kaplan-Meier estimate, log-rank test and its generalization. For parametric inference, includes likelihood estimation and the exponential, Weibull, log-logistic and other relevant distributions. Discusses in detail statistical methods and theory for the proportional hazard models (Cox model), with extensions to time-dependent covariates. Includes clinical and epidemiological examples (through class presentations). Introduces basic concepts and methods for competing risks data, including the cause-specific hazard models and other models based of cumulative incidence function (CIF). Illustrates various statistical procedures (through homework assignments).
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