Mixture cure semiparametric additive hazard models under partly interval censoring — a penalized likelihood approach

Survival analysis can sometimes involve individuals who will not experience the event of interest, forming what is known as the “cured group”. Identifying such individuals is not always possible beforehand, as they provide only right-censored data. Ignoring the presence of the cured group can introd...

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Veröffentlicht in:	Statistics and computing Jg. 35; H. 4
Hauptverfasser:	Li, Jinqing, Ma, Jun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.08.2025 Springer Nature B.V
Schlagworte:	Algorithms Artificial Intelligence Censored data (mathematics) Computer Science Original Paper Probability and Statistics in Computer Science Regression coefficients Statistical Theory and Methods Statistics and Computing/Statistics Programs Interval censoring Automatic smoothing Mixture cure model Additive hazards model Maximum penalized likelihood estimation
ISSN:	0960-3174, 1573-1375
Online-Zugang:	Volltext
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