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) . 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.


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install.packages("eventglm")

1.0.2 by Michael C Sachs, 2 months ago


https://sachsmc.github.io/eventglm/


Report a bug at https://github.com/sachsmc/eventglm/issues/


Browse source code at https://github.com/cran/eventglm


Authors: Michael C Sachs [aut, cre] , Erin E Gabriel [aut] , Morten Overgaard [ctb] (Corrected variance calculation) , Thomas A Gerds [ctb] (Fast computation of leave one out cumulative incidence) , Terry Therneau [ctb] (Restricted mean computation)


Documentation:   PDF Manual  


GPL-3 license


Imports survival, sandwich, stats

Suggests testthat, prodlim, knitr, rmarkdown, rio, data.table


See at CRAN