The R Journal: article published in 2021, volume 13:1

npcure: An R Package for Nonparametric Inference in Mixture Cure Models
Ana López-Cheda, M. Amalia Jácome and Ignacio López-de-Ullibarri , The R Journal (2021) 13:1, pages 21-41.

Abstract Mixture cure models have been widely used to analyze survival data with a cure fraction. They assume that a subgroup of the individuals under study will never experience the event (cured subjects). So, the goal is twofold: to study both the cure probability and the failure time of the uncured individuals through a proper survival function (latency). The R package npcure implements a completely nonparametric approach for estimating these functions in mixture cure models, considering right-censored survival times. Nonparametric estimators for the cure probability and the latency as functions of a covariate are provided. Bootstrap bandwidth selectors for the estimators are included. The package also implements a nonparametric covariate significance test for the cure probability, which can be applied with a continuous, discrete, or qualitative covariate.

Received: 2019-07-19; online 2021-06-07, supplementary material, (2.3 KiB)
CRAN packages: smcure, NPHMC, flexsurvcure, rcure, geecure, miCoPTCM, mixcure, GORcure, intercure, npcure, condSURV, prodlim, survidm, KMsurv
CRAN Task Views implied by cited CRAN packages: Survival

This article and supplementary materials are licensed under a Creative Commons Attribution 4.0 International license.

@article{RJ-2021-027,
  author = {Ana López-Cheda and M. Amalia Jácome and Ignacio López-de-
          Ullibarri},
  title = {{npcure: An R Package for Nonparametric Inference in Mixture
          Cure Models}},
  year = {2021},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2021-027},
  url = {https://doi.org/10.32614/RJ-2021-027},
  pages = {21--41},
  volume = {13},
  number = {1}
}