This course covers analytic and computational methods for modeling and regression analysis in the biomedical sciences. Emphasis is on fitting exploratory and inferential models to data in epidemiology and clinical trials. Topics include tabular and graphical summary; the linear, logistic and Poisson regression models; the Kaplan-Meier method and Cox proportional hazards analysis; power calculation; estimation of effect size. Analyses are presented and completed using R and SAS software packages. Lecture and laboratory exercises are structured around worked examples from the recent biomedical literature. Acquired competency in statistical programming is a major focus of this course. 3 cr, Spring sem.

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