Package: eventglm 1.4.4
eventglm: Regression Models for Event History Outcomes
A user friendly, easy to understand way of doing event history regression for marginal estimands of interest, including the cumulative incidence and the restricted mean survival, using the pseudo observation framework for estimation. For a review of the methodology, see Andersen and Pohar Perme (2010) <doi:10.1177/0962280209105020> or Sachs and Gabriel (2022) <doi:10.18637/jss.v102.i09>. The interface uses the well known formulation of a generalized linear model and allows for features including plotting of residuals, the use of sampling weights, and corrected variance estimation.
Authors:
eventglm_1.4.4.tar.gz
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eventglm_1.4.4.tgz(r-4.4-x86_64)eventglm_1.4.4.tgz(r-4.4-arm64)eventglm_1.4.4.tgz(r-4.3-x86_64)eventglm_1.4.4.tgz(r-4.3-arm64)
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eventglm.pdf |eventglm.html✨
eventglm/json (API)
NEWS
# Install 'eventglm' in R: |
install.packages('eventglm', repos = c('https://sachsmc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/sachsmc/eventglm/issues
Last updated 3 months agofrom:3104ac418e. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 06 2024 |
R-4.5-win-x86_64 | OK | Oct 06 2024 |
R-4.5-linux-x86_64 | OK | Oct 06 2024 |
R-4.4-win-x86_64 | OK | Oct 06 2024 |
R-4.4-mac-x86_64 | OK | Oct 06 2024 |
R-4.4-mac-aarch64 | OK | Oct 06 2024 |
R-4.3-win-x86_64 | OK | Oct 06 2024 |
R-4.3-mac-x86_64 | OK | Oct 06 2024 |
R-4.3-mac-aarch64 | OK | Oct 06 2024 |
Exports:cumincglmjackknife.competing.risks2jackknife.survival2leaveOneOut.competing.risksleaveOneOut.competing.risks2leaveOneOut.survivalleaveOneOut.survival2pseudo_aaregpseudo_coxphpseudo_independentpseudo_infjackpseudo_stratifiedrmeanglmSurv
Dependencies:backportsbroomclicpp11dplyrfansigeepackgenericsgluelatticelifecyclemagrittrMASSMatrixpillarpkgconfigpurrrR6rlangsandwichstringistringrsurvivaltibbletidyrtidyselectutf8vctrswithrzoo
Comparison to other software
Rendered fromstata-sas-comparason.Rmd
usingknitr::rmarkdown
on Oct 06 2024.Last update: 2022-09-04
Started: 2020-12-11
Examples of using eventglm and interpreting the results
Rendered fromexample-analysis.Rmd
usingknitr::rmarkdown
on Oct 06 2024.Last update: 2024-02-22
Started: 2020-08-26
Extending eventglm
Rendered fromextenstions.Rmd
usingknitr::rmarkdown
on Oct 06 2024.Last update: 2022-09-04
Started: 2021-01-23