Simulates time-to-event data with type I right censoring using two methods: the inverse CDF method and our proposed memoryless method. The latter method takes advantage of the memoryless property of survival and simulates a separate distribution between change-points. We include two parametric distributions: exponential and Weibull. Inverse CDF method draws on the work of Rainer Walke (2010), <https://www.demogr.mpg.de/papers/technicalreports/tr-2010-003.pdf>.
Version: | 1.2.0 |
Depends: | R (≥ 3.6.0) |
Imports: | plyr (≥ 1.8.5), stats, Hmisc (≥ 4.3.0), knitr (≥ 1.27) |
Suggests: | rmarkdown, testthat |
Published: | 2020-01-20 |
Author: | Camille Hochheimer [aut, cre] |
Maintainer: | Camille Hochheimer <hochheimercj at vcu.edu> |
BugReports: | http://github.com/camillejo/cpsurvsim/issues |
License: | GPL (≥ 3) |
URL: | http://github.com/camillejo/cpsurvsim |
NeedsCompilation: | no |
Citation: | cpsurvsim citation info |
CRAN checks: | cpsurvsim results |
Reference manual: | cpsurvsim.pdf |
Vignettes: |
Introduction to cpsurvsim |
Package source: | cpsurvsim_1.2.0.tar.gz |
Windows binaries: | r-devel: cpsurvsim_1.2.0.zip, r-release: cpsurvsim_1.2.0.zip, r-oldrel: cpsurvsim_1.2.0.zip |
macOS binaries: | r-release: cpsurvsim_1.2.0.tgz, r-oldrel: cpsurvsim_1.2.0.tgz |
Old sources: | cpsurvsim archive |
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