multilevelMatching: Propensity Score Matching and Subclassification in Observational Studies with Multi-Level Treatments

Implements methods to estimate causal effects from observational studies when there are 2+ distinct levels of treatment (i.e., "multilevel treatment") using matching estimators, as introduced in Yang et al. (2016) <doi:10.1111/biom.12505>. Matching on covariates, and matching or stratification on modeled propensity scores, are available. These methods require matching on only a scalar function of generalized propensity scores.

Version: 1.0.0
Depends: R (≥ 3.1.2)
Imports: Matching (≥ 4.8-3.4), MASS (≥ 7.3-35), nnet (≥ 7.3-8), boot (≥ 1.3-13)
Suggests: knitr, rmarkdown, testthat, rprojroot
Published: 2019-05-08
Author: Shu Yang [aut], Brian G. Barkley ORCID iD [aut, cre]
Maintainer: Brian G. Barkley <BarkleyBG at outlook.com>
BugReports: https://github.com/shuyang1987/multilevelMatching/issues
License: GPL-2
URL: https://shuyang1987.github.io/multilevelMatching/
NeedsCompilation: no
Materials: README NEWS
CRAN checks: multilevelMatching results

Downloads:

Reference manual: multilevelMatching.pdf
Vignettes: multilevelMatching-v1.0.0
Package source: multilevelMatching_1.0.0.tar.gz
Windows binaries: r-devel: multilevelMatching_1.0.0.zip, r-devel-gcc8: multilevelMatching_1.0.0.zip, r-release: multilevelMatching_1.0.0.zip, r-oldrel: multilevelMatching_1.0.0.zip
OS X binaries: r-release: multilevelMatching_1.0.0.tgz, r-oldrel: multilevelMatching_1.0.0.tgz

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