references: - id: shen2009 title: A Semiparametric Regression Cure Model for Interval-Censored Data author: - family: Liu given: Hao - family: Shen given: Yu container-title: Journal of the American Statistical Association volume: 104 issue: 487 page: 1168-1178 type: article-journal issued: year: 2009
family: Zhou given: Feifei container-title: Biometrical Journal volume: 55 issue: 5 page: 771-788 type: article-journal issued: year: 2013
id: lam2014 title: Semiparametric analysis of clustered interval-censored survival data with a cure fraction author:
knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "README-" )
The intercure package provides R implementations for different cure rate models to interval censored data. The goal is to estimate the effects of each given covariate using different specifications and computing the estimated cure fraction with it. For simulation and illustrative examples, the package also provides functions to generate a dataset using one of the cure rate specification.
Two models for interval censored data are considered on this package: the bounded cumulative hazard model proposed on @shen2009; the frailty model proposed on @lam2013, with its extension to clustered data presented on @lam2014.
devtools::install_github("JBrettas/intercure")
To fit a cure rate model:
To generate datasets:
*** NOTE: At the current version, there is a issue regarding the convergence of the expected likelihood in the inter_bch
function. As it provides reasonable estimates of the thetas and the cure fraction, which can be checked via synthetic data, I am keeping the function available for use.
Click here for a tutorial on how to use the package.
My greatest thanks goes to Professor Lam, who gave me help on theorical details of the frailty model and its implementation. Also, my special thanks to Professor Shen, for all the answered doubts and for sharing the original C routine. And of course to Professor Tunes, who greatly oriented me on my master's degree.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.