ipwCoxCSV: Corrected Sandwich Inference for Inverse Probability Weighted Cox Models

An implementation of the corrected sandwich variance (CSV) method for inverse probability weighted (IPW) Cox models described in Shu et al (2021) <doi:10.1111/biom.13332>. The method accounts for the uncertainty in estimating propensity score weights to improve variance and confidence interval estimation for adjusted marginal hazard ratios (HRs) in observational and randomized studies. The package supports estimation of the average treatment effect (ATE) using conventional and stabilized ATE weights, and the average treatment effect in the treated (ATT) using ATT weights, for both independent and clustered data. Propensity scores are estimated using logistic regression.

Version:	1.1
Imports:	survival, stats
Published:	2026-08-02
DOI:	10.32614/CRAN.package.ipwCoxCSV
Author:	Di Shu [aut, cre], Rui Wang [aut]
Maintainer:	Di Shu <shudi1991 at gmail.com>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	no
Materials:	NEWS
CRAN checks:	ipwCoxCSV results

Documentation:

Reference manual:

ipwCoxCSV.html , ipwCoxCSV.pdf

Downloads:

Package source:	ipwCoxCSV_1.1.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
Old sources:	ipwCoxCSV archive

Linking:

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