Fitting Flexible Smooth-in-Time Hazards and Risk Functions via Logistic and Multinomial Regression

Implements the case-base sampling approach of Hanley and Miettinen (2009) , Saarela and Arjas (2015) , and Saarela (2015) , for fitting flexible hazard regression models to survival data with single event type or multiple competing causes via logistic and multinomial regression. From the fitted hazard function, cumulative incidence, risk functions of time, treatment and profile can be derived. This approach accommodates any log-linear hazard function of prognostic time, treatment, and covariates, and readily allows for non-proportionality. We also provide a plot method for visualizing incidence density via population time plots.


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0.1.0 by Sahir Bhatnagar, 5 months ago

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Authors: Sahir Bhatnagar [aut, cre] (, Maxime Turgeon [aut] (, Olli Saarela [aut] (, James Hanley [aut] (

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports data.table, ggplot2, methods, survival, VGAM

Suggests eha, knitr, rmarkdown, splines, testthat

See at CRAN