Description: 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.
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. 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.