Comprehensive toolkit for addressing selection bias in binary disease models across diverse non-probability samples, each with unique selection mechanisms. It utilizes Inverse Probability Weighting (IPW) and Augmented Inverse Probability Weighting (AIPW) methods to reduce selection bias effectively in multiple non-probability cohorts by integrating data from either individual-level or summary-level external sources. The package also provides a variety of variance estimation techniques. Please refer to Kundu et al. <doi:10.48550/arXiv.2412.00228>.
| Version: | 0.0.2.0 |
| Depends: | R (≥ 4.0.0) |
| Imports: | dplyr (≥ 1.0.0), magrittr, MASS, nleqslv (≥ 3.3.2), xgboost (≥ 1.4.1), survey (≥ 4.1.0), stats, nnet (≥ 7.3-17), simplexreg (≥ 0.1.6) |
| Published: | 2025-01-20 |
| DOI: | 10.32614/CRAN.package.EHRmuse |
| Author: | Ritoban Kundu [aut], Michael Kleinsasser [cre] |
| Maintainer: | Michael Kleinsasser <biostat-cran-manager at umich.edu> |
| BugReports: | https://github.com/Ritoban1/EHRmuse/issues |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://github.com/Ritoban1/EHRmuse |
| NeedsCompilation: | no |
| CRAN checks: | EHRmuse results |
| Reference manual: | EHRmuse.pdf |
| Package source: | EHRmuse_0.0.2.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: EHRmuse_0.0.2.0.zip, r-oldrel: not available |
| macOS binaries: | r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available |
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