Package: causalCmprsk 2.0.0
Bella Vakulenko-Lagun
causalCmprsk: Nonparametric and Cox-Based Estimation of Average Treatment Effects in Competing Risks
Estimation of average treatment effects (ATE) of point interventions on time-to-event outcomes with K competing risks (K can be 1). The method uses propensity scores and inverse probability weighting for emulation of baseline randomization, which is described in Charpignon et al. (2022) <doi:10.1038/s41467-022-35157-w>.
Authors:
causalCmprsk_2.0.0.tar.gz
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causalCmprsk.pdf |causalCmprsk.html✨
causalCmprsk/json (API)
| # Install 'causalCmprsk' in R: |
| install.packages('causalCmprsk', repos = c('https://bella2001.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/bella2001/causalcmprsk/issues
Last updated 1 years agofrom:af47e89026. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 27 2024 |
| R-4.5-win | OK | Oct 27 2024 |
| R-4.5-linux | OK | Oct 27 2024 |
| R-4.4-win | OK | Oct 27 2024 |
| R-4.4-mac | OK | Oct 27 2024 |
| R-4.3-win | OK | Oct 27 2024 |
| R-4.3-mac | OK | Oct 27 2024 |
Exports:fit.coxfit.nonparget.numAtRiskget.pointEstget.weights
Dependencies:clicodetoolsdata.tabledoParallelforeachglueinlineiteratorslatticelifecyclemagrittrMatrixpurrrrlangsurvivalvctrs
