Arbeitspapier
Censored quantile regression survival models with a cure proportion
A new quantile regression model for survival data is proposed that permits a positive proportion of subjects to become unsusceptible to recurrence of disease following treatment or based on other observable characteristics. In contrast to prior proposals for quantile regression estimation of censored survival models, we propose a new "data augmentation" approach to estimation. Our approach has computational advantages over earlier approaches proposed by Wu and Yin (2013, 2017). We compare our method with the two estimation strategies proposed by Wu and Yin and demonstrate its advantageous empirical performance in simulations. The methods are also illustrated with data from a Lung Cancer survival study.
- Sprache
-
Englisch
- Erschienen in
-
Series: cemmap working paper ; No. CWP56/19
- Klassifikation
-
Wirtschaft
- Thema
-
Survival data
cure proportion
quantile regression
mixture models
data augmentation
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Narisetty, Naveen
Koenker, Roger
- Ereignis
-
Veröffentlichung
- (wer)
-
Centre for Microdata Methods and Practice (cemmap)
- (wo)
-
London
- (wann)
-
2019
- DOI
-
doi:10.1920/wp.cem.2019.5619
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:45 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Narisetty, Naveen
- Koenker, Roger
- Centre for Microdata Methods and Practice (cemmap)
Entstanden
- 2019
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