Nonparametric latency estimation for mixture cure models
arXiv:2401.16954 · doi:10.1007/s11749-016-0515-1
Abstract
A nonparametric latency estimator for mixture cure models is studied in this paper. An i.i.d. representation is obtained, the asymptotic mean squared error of the latency estimator is found, and its asymptotic normality is proven. A bootstrap bandwidth selection method is introduced and its efficiency is evaluated in a simulation study. The proposed methods are applied to a dataset of colorectal cancer patients in the University Hospital of A Coruña (CHUAC).
24 pages, 3 figures
References in corpus (1)
Cited by in corpus (6)
- Nonparametric incidence estimation and bootstrap bandwidth selection in mixture cure models
- Cure models to estimate time until hospitalization due to COVID-19
- Nonparametric covariate hypothesis tests for the cure rate in mixture cure models
- A product-limit estimator of the conditional survival function when cure status is partially known
- npcure: An R Package for Nonparametric Inference in Mixture Cure Models
- Estimating lengths-of-stay of hospitalised COVID-19 patients using a non-parametric model: a case study in Galicia (Spain)