RobustAFT: Robust Estimation of AFT Model with High-dimensional Covariates

A unified Expectation-Maximization approach combined with the L1-norm (or sparse group lasso) penalty to perform variable selection and obtain parameter estimation simultaneously for the accelerated failure time model with right-censored survival data.

Requirement on R version

We require the R version >=4.0.3 due to another package used in this package.

Setup

To install the most up-to-date version, run the following command in R

library(devtools)
install_github("muxuanliang/RobustAFT")

References:

• Yi Li, Muxuan Liang, Lu Mao, Sijian Wang (2020). Robust Estimation and Variable Selection for the Accelerated Failure Time Model.