Advanced Applied Biostatistical Methods II

Catalog description

This course provides an advanced introduction to general linear models and the concept of experimental designs. Topics include linear regression models, analysis of variance, mixed-effects models, generalized linear models (GLM) including binary, multinomial responses and log-linear models, basic models for survival analysis and regression models for censored survival data, and model assessment, validation, and prediction. Core concepts are mastered through statistical methods application and analysis of practical research problems encountered by program faculty and demonstrated in practicum experiences in concert with BIOSTAT 706/BIOSTAT 706A. Computational examples and exercises will use the SAS and R packages. Director of Graduate Studies permission is required. Credits: 3