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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.
Getting started
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Package details |
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| Author | Di Shu <shudi1991@gmail.com>, Rui Wang <rwang@hsph.harvard.edu> |
| Maintainer | Di Shu <shudi1991@gmail.com> |
| License | GPL (>= 2) |
| Version | 1.0 |
| Package repository | View on CRAN |
| Installation |
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