Package: eventglm 1.4.5

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:Michael C Sachs [aut, cre], Erin E Gabriel [aut], Morten Overgaard [ctb], Thomas A Gerds [ctb], Terry Therneau [ctb]

eventglm_1.4.5.tar.gz
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eventglm_1.4.5.tgz(r-4.5-emscripten)
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

Pkgdown/docs site:https://sachsmc.github.io

Datasets:
  • colon - Chemotherapy for Stage B/C colon cancer
  • mgus2 - Monoclonal gammopathy data

On CRAN:

Conda:

5.73 score 5 stars 1 packages 24 scripts 300 downloads 14 exports 29 dependencies

Last updated from:c112fcaf02. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK158
linux-devel-x86_64OK156
source / vignettesOK221
linux-release-arm64OK153
linux-release-x86_64OK156
macos-release-arm64OK167
macos-release-x86_64OK306
macos-oldrel-arm64OK177
macos-oldrel-x86_64OK322
windows-develOK121
windows-releaseOK98
windows-oldrelOK114
wasm-releaseOK131

Exports:cumincglmjackknife.competing.risks2jackknife.survival2leaveOneOut.competing.risksleaveOneOut.competing.risks2leaveOneOut.survivalleaveOneOut.survival2pseudo_aaregpseudo_coxphpseudo_independentpseudo_infjackpseudo_stratifiedrmeanglmSurv

Dependencies:backportsbroomclicpp11dplyrgeepackgenericsgluelatticelifecyclemagrittrMASSMatrixpillarpkgconfigpurrrR6rlangsandwichstringistringrsurvivaltibbletidyrtidyselectutf8vctrswithrzoo

Comparison to other software

Rendered fromstata-sas-comparason.Rmdusingknitr::rmarkdownon Apr 01 2026.

Last update: 2022-09-04
Started: 2020-12-11

Examples of using eventglm and interpreting the results

Rendered fromexample-analysis.Rmdusingknitr::rmarkdownon Apr 01 2026.

Last update: 2024-02-22
Started: 2020-08-26

Extending eventglm

Rendered fromextenstions.Rmdusingknitr::rmarkdownon Apr 01 2026.

Last update: 2022-09-04
Started: 2021-01-23

Readme and manuals

Help Manual

Help pageTopics
Compute inverse probability of censoring weights pseudo observationscalc_ipcw_pos
Error check censoring modelcheck_mod_cens
Chemotherapy for Stage B/C colon cancercolon
Confidence Intervals for pseudoglm Model Parametersconfint.pseudoglm
Generalized linear models for cumulative incidencecumincglm
Regression Models for Event History Outcomeseventglm
Utility to get jackknife pseudo observations of cumulative incidenceget_pseudo_cuminc
Utility to get jackknife pseudo observations of restricted meanget_pseudo_rmean
Compute jackknife pseudo-observations of the cause-specific cumulative incidence for competing risksjackknife.competing.risks2
Compute jackknife pseudo-observations of the survival functionjackknife.survival2
Compute jackknife pseudo-observations of the cause-specific cumulative incidence for competing risksleaveOneOut.competing.risks
Compute jackknife pseudo-observations of the cause-specific cumulative incidence for competing risksleaveOneOut.competing.risks2
Compute leave one out jackknife contributions of the survival functionleaveOneOut.survival
Compute leave one out jackknife contributions of the survival functionleaveOneOut.survival2
Match cause specification against model responsematch_cause
Monoclonal gammopathy datamgus2
Print method for pseudoglmprint.pseudoglm
Compute censoring weighted pseudo observationspseudo_aareg
Compute censoring weighted pseudo observationspseudo_coxph
Compute pseudo observations under independent censoringpseudo_independent
Compute infinitesimal jackknife pseudo observationspseudo_infjack
Compute pseudo-observations for the restricted mean survivalpseudo_rmst2
Compute pseudo observations using stratified jackknifepseudo_stratified
Pseudo-observation scaled residualsresiduals.pseudoglm
Generalized linear models for the restricted mean survivalrmeanglm
Summary methodsummary.pseudoglm
Compute covariance matrix of regression coefficient estimatesvcov.pseudoglm