Biostatistics

MDCH 611 (formerly MDSC 643.02): Biostatistics II: Models for Health Outcomes

Description: Extends the fundamental concepts to modelling health outcomes using modern regression analysis techniques. Logistic and linear regressions, and their extensions, are covered in detail. The rationale, formulation, and statistical assumptions underlying each regression technique are discussed. Methods for selecting and assessing models are included. Additional topics include a brief introduction to models used in the analysis of repeated measures, longitudinal studies, and time-to-event data. STATA statistical software is used to analyze data.

Prerequisite: MDCH 610 or MDSC 643.01 or a graduate-level course in (bio)statistics. Required course for Biostatistics & Epidemiology specializations.

 

MDCH 612 (formerly MDSC 643.03): Biostatistics III: Models for Repeated Measures Studies and Time-to-Event Studies

Description: Discusses techniques for analyzing data collected at more than one point in time (repeated measures) and time-to-event (survival) data. Topics include generalized linear models (GLM), generalized additive models (GAM), Poisson regression, generalized estimating equations (GEE), and proportional hazards regression with time-varying covariates. STATA statistical software is used to analyze data.

Prerequisite: MDCH 611 or MDSC 643.02 

 

MDCH 710 (formerly MDSC 751.03): Advanced Topics in Biostatistics 


Description: Advanced topics and methods used in Biostatistics. 


Prerequisite: Consent of Instructor.