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matchMulti (version 1.0)

Optimal Multilevel Matching using a Network Algorithm

Description

Performs multilevel matches for data with cluster-level treatments and individual-level outcomes using a network optimization algorithm. Functions for checking balance at the cluster and individual levels are also provided, as are methods for permutation-inference-based outcome analysis.

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Version

Install

install.packages('matchMulti')

Monthly Downloads

627

Version

1.0

License

MIT + file LICENSE

Maintainer

Samuel Pimentel

Last Published

February 19th, 2016

Functions in matchMulti (1.0)

rematchSchools

Repeat School Match Only
matchMulti-package

matchMulti
assembleMatch

Collect Matched Samples
pairmatchelastic

Optimal Subset Matching without Balance Constraints
ci_func

Outcome analysis.
sdiff

Balance Measures
matchStudents

Compute Student Matches for all Pairs of Schools
is.binary

Check if a variable is binary
agg

Extract School-Level Covariates
pval_func

Outcome analysis.
smahal

Robust Mahalanobis Distance
students2schools

Aggregate Student Data into School Data
balanceTable

Create Balance Table
balanceMulti

Performs balance checking after multilevel matching.
resolve.cols

Ensure Dataframes Share Same Set Columns
matchMultioutcome

Performs an outcome analysis after multilevel matching.
matchMultisens

Rosenbaum Bounds after Multilevel Matching
matchMulti

A function that performs multilevel matching.
match2distance

Compute School Distance from a Student Match
catholic_schools

1980 and 1982 High School and Beyond Data
pe_func

Outcome analysis.
handleNA

Handle Missing Values
matchSchools

Match Schools on Student-based Distance