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survivalMPLdc: Penalised Likelihood for Survival Analysis with Dependent Censoring

survivalMPLdc

The survivalMPLdc package provides the estimating and plotting function for the Cox hazard models under dependent right censoring using maximum penalised likelihood method Xu et al (2018).

The survivalMPLdc currently only supports proportional hazard models. The future work can extend the proposed method to other semi-parametric hazard model, i.e. the accelerate failure or additive hazard models. Other type of censoring, i.e. interval censoring and even time-dependent covariates can be considered.

Installation

Stable release on CRAN

The survivalMPLdc package can be installed from CRAN.

install.packages("survivalMPLdc")
library("survivalMPLdc")

Development version on Github

You can use the devtools package to install the development version of survivalMPLdc from GitHub:

# install.packages("devtools")
devtools::install_github("Kenny-Jing-Xu/survivalMPLdc")
library(survivalMPLdc)

Usage

A reference manual is available at kenny-jing-xu.github.io/survivalMPLdc.

Citation

Xu, J., Ma, J. and Fung, T. (2020). survivalMPLdc: Survival Analysis under Dependent Right Censoring using Maximum Penalised Likelihood. R package version 0.1.1.

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Version

Install

install.packages('survivalMPLdc')

Monthly Downloads

127

Version

0.1.1

License

GPL-3

Maintainer

Jing Xu

Last Published

October 24th, 2020

Functions in survivalMPLdc (0.1.1)

plot.coxph_mpl_dc

Plot a baseline hazard estimates from coxph_mpl_dc Object
coxph_mpl_dc

Fit Cox Proportional Hazard Regression Model under dependent right censoring via MPL and Archimedean Copulas
coxph_mpl_dc.control

Ancillary arguments for controlling the outputs of coxph_mpl_dc
surv_data_dc

Generate a sample of time to event dataset with dependent right censoring under an Archimedean copula
coef.coxph_mpl_dc

Extract regression coefficients of a coxph_mpl_dc Object
PRIME

PRIME data set
survivalMPLdc-package

Penalised Likelihood for Survival Analysis with Dependent Censoring