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rsurv  

Random Generation of Survival Data
View on CRAN: Click here


Download and install rsurv package within the R console
Install from CRAN:
install.packages("rsurv")

Install from Github:
library("remotes")
install_github("cran/rsurv")

Install by package version:
library("remotes")
install_version("rsurv", "0.0.2")



Attach the package and use:
library("rsurv")
Maintained by
Fabio Demarqui
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-06-06
Latest Update: 2024-06-06
Description:
Random generation of survival data from a wide range of regression models, including accelerated failure time (AFT), proportional hazards (PH), proportional odds (PO), accelerated hazard (AH), Yang and Prentice (YP), and extended hazard (EH) models. The package 'rsurv' also stands out by its ability to generate survival data from an unlimited number of baseline distributions provided that an implementation of the quantile function of the chosen baseline distribution is available in R. Another nice feature of the package 'rsurv' lies in the fact that linear predictors are specified via a formula-based approach, facilitating the inclusion of categorical variables and interaction terms. The functions implemented in the package 'rsurv' can also be employed to simulate survival data with more complex structures, such as survival data with different types of censoring mechanisms, survival data with cure fraction, survival data with random effects (frailties), multivariate survival data, and competing risks survival data. Details about the R package 'rsurv' can be found in Demarqui (2024) <doi:10.48550/arXiv.2406.01750>.
How to cite:
Fabio Demarqui (2024). rsurv: Random Generation of Survival Data. R package version 0.0.2, https://cran.r-project.org/web/packages/rsurv. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.0.1 (2024-06-06 19:00)
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Complete documentation for rsurv
Functions, R codes and Examples using the rsurv R package
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