Implements the case-base sampling approach of Hanley and Miettinen (2009) <doi:10.2202/1557-4679.1125>, Saarela and Arjas (2015) <doi:10.1111/sjos.12125>, and Saarela (2015) <doi:10.1007/s10985-015-9352-x>, 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.
Version: | 0.1.0 |
Depends: | R (≥ 3.3.1) |
Imports: | data.table, ggplot2, methods, survival, VGAM |
Suggests: | eha, knitr, rmarkdown, splines, testthat |
Published: | 2017-04-28 |
Author: | Sahir Bhatnagar [aut, cre] (http://sahirbhatnagar.com/), Maxime Turgeon [aut] (http://turgeonmaxime.github.io/), Olli Saarela [aut] (http://individual.utoronto.ca/osaarela/), James Hanley [aut] (http://www.medicine.mcgill.ca/epidemiology/hanley/) |
Maintainer: | Sahir Bhatnagar <sahir.bhatnagar at gmail.com> |
BugReports: | https://github.com/sahirbhatnagar/casebase/issues |
License: | MIT + file LICENSE |
URL: | http://sahirbhatnagar.com/casebase/ |
NeedsCompilation: | no |
Citation: | casebase citation info |
Materials: | README NEWS |
CRAN checks: | casebase results |
Reference manual: | casebase.pdf |
Vignettes: |
Competing risk analysis Population Time Plots Introduction to casebase sampling |
Package source: | casebase_0.1.0.tar.gz |
Windows binaries: | r-devel: casebase_0.1.0.zip, r-release: casebase_0.1.0.zip, r-oldrel: casebase_0.1.0.zip |
OS X El Capitan binaries: | r-release: casebase_0.1.0.tgz |
OS X Mavericks binaries: | r-oldrel: casebase_0.1.0.tgz |
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