Category 8: Standards for Causal Inference Methods
Learning Objectives
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.
Learning Modules
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
Module 1: Introduction
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Module 2: Objectives
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Module 3a: Defining Causal Effects
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Module 3b: Confounding, Randomized Experiments, and Nonexperimental Studies
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Module 4: Planning a Nonexperimental Study
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Module 5: Common Nonexperimental Study Designs
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Module 6a: Considerations When Using Propensity Score Methods
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Module 6b: Example of Propensity Score Approach
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Module 7a: Considerations When Using Instrumental Variables Methods
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Module 7b: Example of Instrumental Variable Analysis
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Module 8: Sensitivity Analysis
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Module 9: More Complex Temporal Settings
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Module 10: Key Points
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Category 8 Self-Assessment
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Posted: February 2016
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