Overview | Change in Changes — cic() | Quantile Difference-in-Differences — qdid() | Panel QTT — panel_qtt() | Distributional DiD — ddid() | Mean Difference-in-Differences — mdid() | Lagged-Outcome Unconfoundedness — lou_qtt() | Summary | References

What are Quantile Treatment Effects? | Random assignment | Unconfoundedness | QTT under unconfoundedness | Reading the output | References

Introduction | QTT curve estimation | Overall QTT curve | Dynamic QTT — event-study by quantile | ATT and event-study summary | Comparing estimators | Repeated cross sections | Inference notes | References

Introduction | Examples with simulated data | Estimating Group-Time Average Treatment Effects | Other features of the did package | Adjustments for Multiple Hypothesis Testing | Aggregating group-time average treatment effects | Simple Aggregation | Dynamic Effects and Event Studies | Group-Specific Effects | Calendar Time Effects | Small Group Sizes | Selecting Alternative Control Groups | Repeated cross sections | Unbalanced Panel Data | Alternative Estimation Methods | An example with real data | The Effect of the Minimum Wage on Youth Employment | Common Issues with the did package | Bugs

Introduction | Background | DiD with 2 Periods and 2 Groups | Two way fixed effects regressions | Treatment Effects in Difference in Differences Designs with Multiple Periods | Main Assumptions | Group-Time Average Treatment Effects | Parallel Trends Conditional on Covariates | Aggregating Group-Time Average Treatment Effects | Conclusion | References

Introduction | Setup with all units being eventually treated and homogeneous treatment effect dynamics | Visualizing the DGP | Estimating dynamic treatment effects via TWFE event-study regressions | Using the Callaway and Sant'Anna (2021) framework | Setup with a group that remains untreated at the end of the sample | DGP with a "never-treated" group and homogeneous treatment effect dynamics | Setup with Heterogeneous Treatment Effects | Conclusion | References

Introduction | Common Approaches to Pre-Testing in Applications | Pitfalls with Event Study Regressions | Best Case Scenario for Pre-Testing | Pitfall: Selective Treatment Timing | Conditional Moment Tests | References

Introduction | DiD with Anticipation | Computing Treatment Effects under DiD with Anticipation | Conclusion