QBS 121 Foundations of Biostatistics II: Statistical Regression
We cover the theory and applications of statistical regression, as practiced in biomedical research. We present statistical inference (estimation and hypothesis testing) for linear models, generalized linear models (e.g. logistic and Poisson regression), longitudinal models for repeated measurements, and models for times-to-event (survival analysis). The course emphasizes the primary goals of regression, which are (i) prediction and (ii) causal inference. It also introduces penalized regression for large numbers of predictors and methods for missing data in regression. The statistical software R is used for applications.
(1 unit)
Instructor
Dr. Todd MacKenzie and Dr. Tor Tosteson
Cross Listed Courses
PH 271
Prerequisite
QBS 120 or
QBS 119. Calculus, linear algebra. Programming: Intermediate proficiency in R.