Maximum likelihood estimation of semiparametric mixture component models for competing risks data

DOI10.1111/BIOM.12167zbMath1299.62025OpenAlexW1771164022WikidataQ30801458 ScholiaQ30801458MaRDI QIDQ2927610

Xuelin Huang, Sangbum Choi

Publication date: 4 November 2014

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/biom.12167

zbMATH Keywords

martingaletransformation modelcure modeljoint modelcumulative incidencenonparametric likelihood

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05)

Related Items (5)

Nonparametric estimation for competing risks survival data subject to left truncation and interval censoring ⋮ Efficient semiparametric mixture inferences on cure rate models for competing risks ⋮ Mixture regression models for the gap time distributions and illness-death processes ⋮ Cluster validity indices for mixture hazards regression models ⋮ Accelerated failure time models for the analysis of competing risks

Uses Software

• cmprsk

Cites Work

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• A General Class of Semiparametric Transformation Frailty Models for Nonproportional Hazards Survival Data
• Regression Modeling of Competing Risks Data Based on Pseudovalues of the Cumulative Incidence Function
• Semiparametric analysis of mixture regression models with competing risks data

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