Research Practices
7 practices that improve the credibility of your empirical research, organized by pipeline stage: Design, Estimation, Robustness, and Reporting.
Sensitivity Analysis for Unobservables
How robust are your results to omitted variable bias? Oster (2019) and Cinelli & Hazlett (2020) provide formal answers.
Multiple Hypothesis Testing
Testing many hypotheses inflates false positives. Bonferroni, Holm, BH-FDR, and Romano-Wolf corrections.
Pre-Analysis Plans & Pre-Registration
Commit to your analysis before seeing the results — the antidote to the garden of forking paths.
Randomization Inference
When conventional asymptotics fail — few clusters, unusual randomization — Fisher's exact approach provides valid inference.
Power Analysis & Sample-Size Planning
How large a sample do you need to detect your effect? Power calculations prevent underpowered studies.
Specification Curve Analysis
How much do your results depend on the specific analytical choices you made? Explore the full space of defensible specifications.
Lee Bounds for Attrition
When point identification fails — especially due to differential attrition — informative bounds can still be useful.