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.
Competencies: Students are expected to achieve the following competencies: (1) understand the statistical methods used to analyze correlated and longitudinal data in a variety of settings and with a variety of outcome variables; (2) become well-versed in the application of core statistical techniques in analyzing repeated measures identifying an appropriate design and selecting the statistical methods required to analyze the data; (3) master software (e.g. SAS procedures) to perform longitudinal analyses; (4) develop the knowledge to interpret and communicate the clinical and scientific meaning of the results to both statisticians and clinicians/scientists.