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25 January 2020
Article (Scientific journals)
The nonparametric location-scale mixture cure model
Chown, Justin; Heuchenne, Cédric  ; Van Keilegom, Ingrid
2020 • In TEST, 29, p. 1008-1028
Peer reviewed
 

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Keywords :
Censored data; Cure model; Error distribution function; Nonparametric regression
Abstract :
[en] We propose completely nonparametric methodology to investigate location-scale modeling of two-component mixture cure models that is similar in spirit to accelerated failure time models, where the responses of interest are only indirectly observable due to the presence of censoring and the presence of long-term survivors that are always censored. We use nonparametric estimators of the location-scale model components that depend on a bandwidth sequence to propose an estimator of the error distribution function that has not been considered before in the literature. When this bandwidth belongs to a certain range of undersmoothing bandwidths, the proposed estimator of the error distribution function is root-n consistent. A simulation study investigates the finite sample properties of our approach, and the methodology is illustrated using data obtained to study the behavior of distant metastasis in lymph-node-negative breast cancer patients. © 2019, Sociedad de Estadística e Investigación Operativa.
Disciplines :
Mathematics
Author, co-author :
Chown, Justin;  Fakultät für Mathematik, Ruhr-Universität Bochum, Bochum, Germany
Heuchenne, Cédric ;  Université de Liège - ULiège > HEC Liège : UER > UER Opérations: Statistique appl. à la gest. et à l'économie
Van Keilegom, Ingrid;  ORSTAT, KU Leuven, Louvain, Belgium
Language :
English
Title :
The nonparametric location-scale mixture cure model
Publication date :
2020
Journal title :
TEST
ISSN :
1133-0686
eISSN :
1863-8260
Publisher :
Springer
Volume :
29
Pages :
1008-1028
Peer reviewed :
Peer reviewed
Funders :
Bundesministerium für Bildung und Forschung, BMBF694409European Research Council, ERCSFB 823P7/06German-Israeli Foundation for Scientific Research and Development, GIF

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