Nonparametric latency estimation for mixture cure models

• Published in: Test (Madrid, Spain) Vol. 26; no. 2; pp. 353 - 376
• Main Authors: López-Cheda, Ana, Jácome, M. Amalia, Cao, Ricardo
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01-06-2017; Springer Nature B.V
• Subjects: Asymptotic methods; Cancer; Colorectal cancer; Computer simulation; Economics; Estimating techniques; Finance; Insurance; Management; Mathematics and Statistics; Nonparametric statistics; Normality; Original Paper; Simulation; Statistical Theory and Methods; Statistics; Statistics for Business; Censored data; 62G08 Nonparametric regression (Nonparametric inference); Survival analysis; Bandwidth selection; Bootstrap; Kernel estimation; 62N01 Censored data models (Survival analysis and censored data); 62N02 Estimation (Survival analysis and censored data)
• ISSN: 1133-0686; 1863-8260
• DOI: 10.1007/s11749-016-0515-1

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).