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-4.5)ipwCoxCSV_1.0.zip(r-4.4)ipwCoxCSV_1.0.zip(r-4.3)
ipwCoxCSV_1.0.tgz(r-4.4-any)ipwCoxCSV_1.0.tgz(r-4.3-any)
ipwCoxCSV_1.0.tar.gz(r-4.5-noble)ipwCoxCSV_1.0.tar.gz(r-4.4-noble)
ipwCoxCSV_1.0.tgz(r-4.4-emscripten)ipwCoxCSV_1.0.tgz(r-4.3-emscripten)
ipwCoxCSV.pdf |ipwCoxCSV.html
ipwCoxCSV/json (API)

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

Peer review:

On CRAN:

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

1.00 score 140 downloads 2 exports 3 dependencies

Last updated 5 years agofrom:0e8493b45e. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 17 2024
R-4.5-winOKNov 17 2024
R-4.5-linuxOKNov 17 2024
R-4.4-winOKNov 17 2024
R-4.4-macOKNov 17 2024
R-4.3-winOKNov 17 2024
R-4.3-macOKNov 17 2024

Exports:ipwCoxClusteripwCoxInd

Dependencies:latticeMatrixsurvival