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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