Package: ipwCoxCSV 1.0

ipwCoxCSV: Inverse Probability Weighted Cox Model with Corrected Sandwich Variance

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.

Authors:Di Shu <[email protected]>, Rui Wang <[email protected]>

ipwCoxCSV_1.0.tar.gz
ipwCoxCSV_1.0.zip(r-4.7)ipwCoxCSV_1.0.zip(r-4.6)ipwCoxCSV_1.0.zip(r-4.5)
ipwCoxCSV_1.0.tgz(r-4.6-any)ipwCoxCSV_1.0.tgz(r-4.5-any)
ipwCoxCSV_1.0.tar.gz(r-4.7-any)ipwCoxCSV_1.0.tar.gz(r-4.6-any)
ipwCoxCSV_1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
ipwCoxCSV/json (API)

# Install 'ipwCoxCSV' in R:
install.packages('ipwCoxCSV', repos = c('https://shu-d.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 1 stars 1 scripts 172 downloads 2 exports 3 dependencies

Last updated from:0e8493b45e. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK169
source / vignettesOK169
linux-release-x86_64OK109
macos-release-arm64OK104
macos-oldrel-arm64OK98
windows-develOK77
windows-releaseOK77
windows-oldrelOK89
wasm-releaseOK85

Exports:ipwCoxClusteripwCoxInd

Dependencies:latticeMatrixsurvival