hrIPW: Hazard Ratio Estimation using Cox Model Weighted by the Estimated Propensity Score

Estimates the log hazard ratio associated with a binary exposure using a Cox PH model weighted by the propensity score. Propensity model is estimated using a simple logistic regression. Variance estimation takes into account the propensity score estimation step with the method proposed by Hajage et al. (2018) <doi:10.1002/bimj.201700330>. Both the average treatment effect on the overall (ATE) or the treated (ATT) population can be estimated. For the ATE estimation, both unstabilized and stabilized weights can be used.

Version: 0.1.3
Depends: R (≥ 3.3)
Imports: survival
Suggests: RISCA, boot
Published: 2020-04-13
Author: David Hajage [aut, cre]
Maintainer: David Hajage <david.hajage at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: NEWS
CRAN checks: hrIPW results


Reference manual: hrIPW.pdf


Package source: hrIPW_0.1.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): hrIPW_0.1.3.tgz, r-oldrel (arm64): hrIPW_0.1.3.tgz, r-release (x86_64): hrIPW_0.1.3.tgz, r-oldrel (x86_64): hrIPW_0.1.3.tgz
Old sources: hrIPW archive


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