Cognitive: Explain how causal effects are defined; Describe the benefits of randomized experiments for estimating causal effects; Recognize the danger of confounding in nonexperimental studies; Determine whether there is covariate balance across treatment groups.
Attitudinal: Value careful and thoughtful design of causal inference studies.
Skills: Prepare an analytic plan that clearly states the causal hypothesis of interest, populations, exposures, comparators, and outcomes; Demonstrate the timing of an outcome assessment relative to the initiation and duration of exposure; Choose the strongest study design for estimating causal effects for the question of interest (i.e., randomized designs, self-controlled case series); Show how to balance bias and variance in study design and analysis; Report the key assumptions underlying propensity score and instrumental variable approaches.
This category contains the curriculum Introduction and ten main modules. Learn about the instructors for this curriculum.
- Introductory Lecture: Prepared and presented by Jodi Segal, MD, MPH
- Learning Modules: Prepared by Elizabeth Stuart, PhD, and Scott Zeger, PhD; Presented by Elizabeth Stuart, PhD
Category 8 Self-Assessment
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Posted: February 2016