Part II · Causal Frameworks & Experiments
Module 04. Potential Outcomes & Randomised Trials
Define causal effects precisely, then see why randomisation identifies them and how to do inference right.
Education: evaluating school-voucher lotteries; NSW and HIV-incentive experiments about 6 hours3 lessons
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Lessons
4.1
Potential Outcomes: ATE, ATT, ATU and Selection Bias
- · Write each unit's two potential outcomes and the fundamental problem of causal inference
- · Define and compute the ATE, ATT and ATU in a simulation where both outcomes are visible
- · Decompose a naive difference in means into the ATT plus selection bias
120 min 4 Colab cellsVideo coming soon
4.2
Randomised Experiments: the Voucher Lottery
- · Explain why random assignment removes selection bias
- · Estimate an ATE by difference in means and by regression
- · Check covariate balance and interpret a balance table
120 min 6 Colab cellsVideo coming soon
4.3
Inference for Experiments: Permutation Tests, Clusters and Power
- · Run a randomisation (permutation) test that relies only on the design
- · Analyse a cluster-randomised experiment with clustered standard errors
- · Estimate the effect of incentives on learning HIV status (Thornton, 2008)
120 min 6 Colab cellsVideo coming soon