The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
Implements the navigated weighting (NAWT) proposed by Katsumata (2020) <doi:10.48550/arXiv.2005.10998>, which improves the inverse probability weighting by utilizing estimating equations suitable for a specific pre-specified parameter of interest (e.g., the average treatment effects or the average treatment effects on the treated) in propensity score estimation. It includes the covariate balancing propensity score proposed by Imai and Ratkovic (2014) <doi:10.1111/rssb.12027>, which uses covariate balancing conditions in propensity score estimation. The point estimate of the parameter of interest as well as coefficients for propensity score estimation and their uncertainty are produced using the M-estimation. The same functions can be used to estimate average outcomes in missing outcome cases.
Version: | 0.1.4 |
Depends: | R (≥ 2.10) |
Imports: | MASS |
Suggests: | hypergeo, testthat |
Published: | 2020-07-23 |
DOI: | 10.32614/CRAN.package.nawtilus |
Author: | Hiroto Katsumata [aut, cre] |
Maintainer: | Hiroto Katsumata <hrt.katsumata at gmail.com> |
License: | GPL-3 |
NeedsCompilation: | no |
Materials: | README NEWS |
In views: | MissingData |
CRAN checks: | nawtilus results |
Reference manual: | nawtilus.pdf |
Package source: | nawtilus_0.1.4.tar.gz |
Windows binaries: | r-devel: nawtilus_0.1.4.zip, r-release: nawtilus_0.1.4.zip, r-oldrel: nawtilus_0.1.4.zip |
macOS binaries: | r-release (arm64): nawtilus_0.1.4.tgz, r-oldrel (arm64): nawtilus_0.1.4.tgz, r-release (x86_64): nawtilus_0.1.4.tgz, r-oldrel (x86_64): nawtilus_0.1.4.tgz |
Old sources: | nawtilus archive |
Please use the canonical form https://CRAN.R-project.org/package=nawtilus to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.