Matching

matchit() print(<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).