Description
Fine-Gray Regression via Forward-Backward Scan.
Description
In competing risks regression, the proportional subdistribution hazards (PSH) model is popular for its direct assessment of covariate effects on the cumulative incidence function. This package allows for both penalized and unpenalized PSH regression in linear time using a novel forward-backward scan. Penalties include Ridge, Lease Absolute Shrinkage and Selection Operator (LASSO), Smoothly Clipped Absolute Deviation (SCAD), Minimax Concave Plus (MCP), and elastic net <doi: 10.32614/RJ-2021-010>.
README.md
Introduction
fastcmprsk is an R package for performing Fine-Gray regression via a forward-backward scan algorithm.
Official CRAN release is available here.
NOTE TO USERS: We plan to make monthly/quarterly updates to the package!
What’s New in Version 1.22.1?
- Allows for Fine-Gray regression w.o presence of right censoring.
Features
- Scalable Fine-Gray parameter estimation procedure for large-scale competing risks data.
- Currently supports unpenalized and penalized (LASSO, ridge, SCAD, MCP, elastic-net) regression.
- Can perform CIF estimation with interval/band estimation via bootstrap.
Implementation
fastcmprsk in an R package with most functionality implemented in C. The package uses cyclic coordinate descent to optimize the likelihood function.
Installation
To install the latest development version, install from GitHub.
install.packages("devtools")
devtools::install_github(“erickawaguchi/fastcmprsk”)
System Requirements
Requires R (version 4.0.0 or higher).
User Documentation
- Package manual: Currently unavailable.
- Please cite Kawaguchi et al. (2021).
License
fastcmprsk is licensed under GPL-3.
Development
fastcmprsk is being developed in R Studio.