Co-founder and President Aetion Sharon, United States
1. Course Aim Issues of bias and confounding relate to study design and analysis in the setting of non-random treatment assignment where compared subjects might differ substantially with respect to comorbidities. Failing to address a lack of balance in the covariates between treated and comparison groups can produce confounded estimates of treatment effect. This course aims to describe the use of propensity scores to address confounding in pharmacoepidemiology.
2. Requisites Statement This is an intermediate level course.
Background in epidemiology and logistic regression modelling is assumed.
No precourse work is needed.
3. Course Objectives • Discuss how propensity scores are useful for observational research; • Recognize research conditions where propensity scores offer advantages; and • Explain how propensity scores may be applied in research (restriction, stratification, matching, modeling, and weighting), and the effect of each application on inference.
4. Syllabus Outline Faculty will explain how propensity scores can be used to mitigate confounding through standard observational approaches (restriction, stratification, matching, regression, or weighting).
The advantages and disadvantages of standard adjustment relative to propensity score-based methods will be discussed.
Details of propensity score methodology (variable selection, use, and diagnostics) will also be discussed.