# Nonparametric Preprocessing for Parametric Causal Inference

## Documentation for package ‘MatchIt’ version 4.7.2

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

add_s.weights | Add sampling weights to a 'matchit' object
distance | Propensity scores and other distance measures
euclidean_dist | Compute a Distance Matrix
get_matches | Construct a matched dataset from a 'matchit' object
lalonde | Data from National Supported Work Demonstration and PSID, as analyzed by Dehejia and Wahba (1999).
mahalanobis_dist | Compute a Distance Matrix
match.data | Construct a matched dataset from a 'matchit' object
matchit | Matching for Causal Inference
match_data | Construct a matched dataset from a 'matchit' object
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
plot.matchit | Generate Balance Plots after Matching and Subclassification
plot.matchit.subclass | Generate Balance Plots after Matching and Subclassification
plot.summary.matchit | Generate a Love Plot of Standardized Mean Differences
print.summary.matchit | View a balance summary of a 'matchit' object
print.summary.matchit.subclass | View a balance summary of a 'matchit' object
rbind.getmatches | Append matched datasets together
rbind.matchdata | Append matched datasets together
robust_mahalanobis_dist | Compute a Distance Matrix
scaled_euclidean_dist | Compute a Distance Matrix
summary.matchit | View a balance summary of a 'matchit' object
summary.matchit.subclass | View a balance summary of a 'matchit' object