IPWpn: Inverse-Propensity-Weighting for Partially Nested Designs

Use inverse-propensity-weighted estimation approaches to estimating the treatment effect from a partially nested design where one study arm (the treatment arm) is nested and the other study arm (the control arm) is not. Two estimators are provided: IPW mean difference and IPW multilevel modeling. <https://github.com/xliu12/IPWpn>.

Version: 0.1.0
Depends: R (≥ 2.10)
Imports: MplusAutomation, tidyverse, mvtnorm, stats, utils, dplyr, tibble, tidyr
Suggests: knitr, rmarkdown, testthat (≥ 2.0.0)
Published: 2021-04-13
Author: Xiao Liu
Maintainer: Xiao Liu <xliu19 at nd.edu>
License: GPL-2
NeedsCompilation: no
CRAN checks: IPWpn results


Reference manual: IPWpn.pdf
Vignettes: IPWpn-vignette


Package source: IPWpn_0.1.0.tar.gz
Windows binaries: r-devel: IPWpn_0.1.0.zip, r-release: IPWpn_0.1.0.zip, r-oldrel: IPWpn_0.1.0.zip
macOS binaries: r-release (arm64): IPWpn_0.1.0.tgz, r-oldrel (arm64): IPWpn_0.1.0.tgz, r-release (x86_64): IPWpn_0.1.0.tgz, r-oldrel (x86_64): IPWpn_0.1.0.tgz


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