Purpose | Choosing an estimator | Basic R workflow | Reading the main options | Treatment categories | Partial identification | Covariates | Inference | Translating from Stata | Practical checklist | References

Introduction | Simulated Data Example | Basic Estimation | Wald-DID, Wald-TC, and Wald-CIC | Extracting Results Programmatically | Core Stata Parity Check | Key Parity Points | 1. User-Controlled Bootstrap Seed | 2. Design Restrictions | 3. Partial Identification Bounds | 4. Equality Tests | Covariate Adjustment | Parametric Adjustment with modelx | Nonparametric Adjustment with Sieves | LQTE Estimation | Multi-Period Designs | Bootstrap Diagnostics | References

Introduction | Data Preparation | Loading the Data | Constructing the Analysis Sample | Constructing Group Variables | Two-Arm Estimation | Arm 1: Districts with Increasing Education (g* = 1 vs g* = 0) | Arm 2: Districts with Decreasing Education (g* = -1 vs g* = 0) | Aggregating Results | Comparison with Stata | References