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An implementation of corrected sandwich variance (CSV) estimation method for making inference of marginal hazard ratios (HR) in inverse probability weighted (IPW) Cox model without and with clustered data, proposed by Shu, Young, Toh, and Wang (2019) in their paper under revision for Biometrics. Both conventional inverse probability weights and stabilized weights are implemented. Logistic regression model is assumed for propensity score model.
| Version: | 1.0 |
| Imports: | survival, stats |
| Published: | 2019-10-09 |
| DOI: | 10.32614/CRAN.package.ipwCoxCSV |
| Author: | Di Shu, Rui Wang |
| Maintainer: | Di Shu <shudi1991 at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | ipwCoxCSV results |
| Reference manual: | ipwCoxCSV.pdf |
| Package source: | ipwCoxCSV_1.0.tar.gz |
| Windows binaries: | r-devel: ipwCoxCSV_1.0.zip, r-release: ipwCoxCSV_1.0.zip, r-oldrel: ipwCoxCSV_1.0.zip |
| macOS binaries: | r-release (arm64): ipwCoxCSV_1.0.tgz, r-oldrel (arm64): ipwCoxCSV_1.0.tgz, r-release (x86_64): ipwCoxCSV_1.0.tgz, r-oldrel (x86_64): ipwCoxCSV_1.0.tgz |
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These binaries (installable software) and packages are in development.
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