Nonparametric covariate hypothesis tests for the cure rate in mixture cure models

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: López-Cheda, Ana, Jácome, M. Amalia, Van Keilegom, Ingrid, Cao, Ricardo
Natura: Preprint
Pubblicazione: 2024
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866914659534110720
author López-Cheda, Ana
Jácome, M. Amalia
Van Keilegom, Ingrid
Cao, Ricardo
author_facet López-Cheda, Ana
Jácome, M. Amalia
Van Keilegom, Ingrid
Cao, Ricardo
contents In lifetime data, like cancer studies, theremay be long term survivors, which lead to heavy censoring at the end of the follow-up period. Since a standard survival model is not appropriate to handle these data, a cure model is needed. In the literature, covariate hypothesis tests for cure models are limited to parametric and semiparametric methods.We fill this important gap by proposing a nonparametric covariate hypothesis test for the probability of cure in mixture cure models. A bootstrap method is proposed to approximate the null distribution of the test statistic. The procedure can be applied to any type of covariate, and could be extended to the multivariate setting. Its efficiency is evaluated in a Monte Carlo simulation study. Finally, the method is applied to a colorectal cancer dataset.
format Preprint
id arxiv_https___arxiv_org_abs_2401_17110
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Nonparametric covariate hypothesis tests for the cure rate in mixture cure models
López-Cheda, Ana
Jácome, M. Amalia
Van Keilegom, Ingrid
Cao, Ricardo
Methodology
In lifetime data, like cancer studies, theremay be long term survivors, which lead to heavy censoring at the end of the follow-up period. Since a standard survival model is not appropriate to handle these data, a cure model is needed. In the literature, covariate hypothesis tests for cure models are limited to parametric and semiparametric methods.We fill this important gap by proposing a nonparametric covariate hypothesis test for the probability of cure in mixture cure models. A bootstrap method is proposed to approximate the null distribution of the test statistic. The procedure can be applied to any type of covariate, and could be extended to the multivariate setting. Its efficiency is evaluated in a Monte Carlo simulation study. Finally, the method is applied to a colorectal cancer dataset.
title Nonparametric covariate hypothesis tests for the cure rate in mixture cure models
topic Methodology
url https://arxiv.org/abs/2401.17110