Title Page | Introduction | The Method | Example 1: Detergent Brand Choice | Example 2: Voters' Preference of Political Parties | References

Introduction | Matching | Nearest Neighbor Matching (method = "nearest") | Optimal Pair Matching (method = "optimal") | Optimal Full Matching (method = "full") | Generalized Full Matching (method = "quick") | Genetic Matching (method = "genetic") | Exact Matching (method = "exact") | Coarsened Exact Matching (method = "cem") | Subclassification (method = "subclass") | Cardinality and Profile Matching (method = "cardinality") | Customizing the Matching Specification | Specifying the propensity score or other distance measure (distance) | Implementing common support restrictions (discard) | Caliper matching (caliper) | Mahalanobis distance matching (mahvars) | Exact matching (exact) | Anti-exact matching (antiexact) | Matching with replacement (replace) | $k$:1 matching (ratio) | Matching order (m.order) | Choosing a Matching Method | Reporting the Matching Specification | References

Introduction | Identifying the estimand | G-computation | Modeling the Outcome | Estimating Standard Errors and Confidence Intervals | Robust and Cluster-Robust Standard Errors | Bootstrapping | Estimating Treatment Effects and Standard Errors After Matching | The Standard Case | Adjustments to the Standard Case | Matching for the ATE | Matching with replacement | Matching without pairing | Propensity score subclassification | Binary outcomes | Survival outcomes | Using Bootstrapping to Estimate Confidence Intervals | The standard bootstrap | The cluster bootstrap | Moderation Analysis | Reporting Results | Common Mistakes | 1. Failing to include weights | 2. Failing to use robust or cluster-robust standard errors | 3. Interpreting conditional effects as marginal effects | References | Code to Generate Data used in Examples

Introduction | Matching | Assessing Balance | Estimating the Effect | Code to Generate Data used in Examples | References

Introduction | Planning | Check Initial Imbalance | Matching | Assessing the Quality of Matches | Trying a Different Matching Specification | Estimating the Treatment Effect | Reporting Results | Conclusion | References

Introduction | Recommendations for Balance Assessment | Recommendations for Balance Reporting | Assessing Balance with MatchIt | summary.matchit() | plot.summary.matchit() | plot.matchit() | Assessing Balance After Subclassification | Assessing Balance with cobalt | bal.tab() | love.plot() | bal.plot() | Conclusion | References

RCT2 | Motivation | Study Design | Data | Overview | Functions | CADErand | CADEreg | CADEparamreg

Study Design | Data | Overview | Functions | CalAPO | Test2SRE | Calpara and Calsamplesize