Description: Fundamental probability and distribution theory needed for statistical inference. Probability, discrete and continuous distributions, expectation, generating functions, limit theorems, transformations, sampling theory.
Prerequisites: BIOSTAT650 and concurrent enrollment in BIOSTAT651
Description: This course provides an overview of statistical models and methodologies for analyzing repeated measures/longitudinal data. The course covers general linear models and linear mixed models for analyzing correlated continuous data, as well as marginal (i.e. GEE), conditional (i.e. generalized linear mixed model) and transition models for analyzing correlated discrete data.