Given a vector of variables of interest for students in a single school,
extracts a single value for the school

internal

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. Details in
Pimentel et al. (2018) <doi:10.1214/17-AOAS1118>. The optmatch
package, which is useful for running many of the provided
functions, may be downloaded from Github at
<https://github.com/markmfredrickson/optmatch> if not available on
CRAN.

Samuel Pimentel

matchMulti

Optimal Multilevel Matching using a Network Algorithm

Luke Keele

Luke Miratrix

Sam Pimentel

Paul Rosenbaum

agg function

<dl><dt>x</dt>
<dd>a vector containing student-level observations for a school. If it
is a factor it must contain only a single level.</dd></dl>

Arguments

Luke Keele, Penn State University, <a href="/link/ljk20%40psu.edu?package=matchMulti&version=1.1.12.1" data-mini-rdoc="matchMulti::ljk20@psu.edu">ljk20@psu.edu</a>
Sam Pimentel, University of California, Berkeley, <a href="/link/spi%40berkeley.edu?package=matchMulti&version=1.1.12.1" data-mini-rdoc="matchMulti::spi@berkeley.edu">spi@berkeley.edu</a>

Author

Extract School-Level Covariates — agg

<dl>

<dt>x</dt>
<dd>a vector containing student-level observations for a school. If it
is a factor it must contain only a single level.</dd>

</dl>

Luke Keele, Penn State University, <a href='mailto:ljk20@psu.edu'>ljk20@psu.edu</a>
Sam Pimentel, University of California, Berkeley, <a href='mailto:spi@berkeley.edu'>spi@berkeley.edu</a>

agg: Extract School-Level Covariates

Description

Usage

Value

Arguments

Author

Details