SUMMER WORKSHOP ON
MODERN APPLIED METHODS IN BIOSTATISTICS
at the University of Toronto, Medical Science Building
August 14 -17, 2006 -- 9 AM to 5 PM

Lecture 5: PROPENSITY SCORE METHODS
Peter Austin
Senior Scientist, Institute for Clinical Evaluative Sciences.
Departments of Public Health Sciences and Health Policy, Management and Evaluation, UToronto

The propensity score is defined as a subject's probability of exposure to a given treatment conditional on their observed characteristics. Propensity score methods are increasingly being used to make causal inferences about treatment effects using observational or non-randomized data. In this session we will describe the propensity score, illustrate how to develop a good propensity score model, methods for determining the performance of the derived propensity score model, and different statistical methods for using the propensity score method to estimate treatment effects.

Instructor:
Peter Austin is a senior scientist at the Institute for Clinical Evaluative Sciences and an Associate Professor in the departments of Public Health Sciences and Health Policy, Management and Evaluation at the University of Toronto. His research is supported by the Natural Sciences and Engineering Research Council (NSERC) and the Canadian Institutes of Health Research (CIHR). His research interests include propensity score methods; hierarchical and multilevel models; Bayesian methods in health care research; flexible regression methods in medical research. He has published several research articles on propensity score methods in the statistical literature.

Contact
Peter Austin, PhD
Senior Scientist, Institute for Clinical Evaluative Sciences.
Associate Professor, Departments of Public Health Sciences and Health
Policy, Management and Evaluation, University of Toronto.

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