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An implementation of the correction methods proposed by Shu and Yi (2017) <doi:10.1177/0962280217743777> for the inverse probability weighted (IPW) estimation of average treatment effect (ATE) with misclassified binary outcomes. Logistic regression model is assumed for treatment model for all implemented correction methods, and is assumed for the outcome model for the implemented doubly robust correction method. Misclassification probability given a true value of the outcome is assumed to be the same for all individuals.
| Version: | 2.1 |
| Imports: | nleqslv, stats |
| Published: | 2019-05-02 |
| DOI: | 10.32614/CRAN.package.ipwErrorY |
| Author: | Di Shu, Grace Y. Yi |
| Maintainer: | Di Shu <shudi1991 at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | ipwErrorY results |
| Reference manual: | ipwErrorY.pdf |
| Package source: | ipwErrorY_2.1.tar.gz |
| Windows binaries: | r-devel: ipwErrorY_2.1.zip, r-release: ipwErrorY_2.1.zip, r-oldrel: ipwErrorY_2.1.zip |
| macOS binaries: | r-release (arm64): ipwErrorY_2.1.tgz, r-oldrel (arm64): ipwErrorY_2.1.tgz, r-release (x86_64): ipwErrorY_2.1.tgz, r-oldrel (x86_64): ipwErrorY_2.1.tgz |
| Old sources: | ipwErrorY archive |
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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.