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Matching

matchit()
Matching for Causal Inference
method_cardinality
Cardinality Matching
method_cem
Coarsened Exact Matching
method_exact
Exact Matching
method_full
Optimal Full Matching
method_genetic
Genetic Matching
method_nearest
Nearest Neighbor Matching
method_optimal
Optimal Pair Matching
method_quick
Fast Generalized Full Matching
method_subclass
Subclassification
distance
Propensity scores and other distance measures
mahalanobis_dist() scaled_euclidean_dist() robust_mahalanobis_dist() euclidean_dist()
Compute a Distance Matrix
add_s.weights()
Add sampling weights to a matchit object

Assessing Balance

summary(<matchit>) summary(<matchit.subclass>) print(<summary.matchit>)
View a balance summary of a matchit object
plot(<summary.matchit>)
Generate a Love Plot of Standardized Mean Differences
plot(<matchit>) plot(<matchit.subclass>)
Generate Balance Plots after Matching and Subclassification

Extracting Matched Data

match.data() get_matches()
Construct a matched dataset from a matchit object
rbind(<matchdata>) rbind(<getmatches>)
Append matched datasets together

Datasets

lalonde
Data from National Supported Work Demonstration and PSID, as analyzed by Dehejia and Wahba (1999).