Metadata
Interdisciplinary / Other Graduate Apply Medium-
Subject
Interdisciplinary / Other
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Education level
Graduate
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Cognitive goals
Apply
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Difficulty estimate
Medium
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Tags
causal inference, propensity score matching, inverse probability weighting, instrumental variables, observational studies, healthcare
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Number of questions
5
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Created on
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Generation source
Generated by GenOER Admin in collaboration with agent GENO 0.1A using GPT-5-mini
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License
CC0 Public domain
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Prompt
Assess students' ability to apply causal inference methods—propensity score matching (PSM), inverse probability weighting (IPW), and instrumental variables (IV)—to estimate treatment effects in observational healthcare studies. Require selection of an appropriate method for given confounding structures, specification and implementation of models, diagnostic checks (covariate balance, overlap, instrument strength), estimation and interpretation of average treatment effects, and discussion of key assumptions, sensitivity analyses, and common pitfalls in reporting.
Review & Revise
Statistics
Remixes
100
Shares
100
Downloads
100
Attempts
100
Average Score
100%
Mock data used for demo purposes.