Analysis of a semiparametric mixture model for competing risks
DOI10.1007/S10463-009-0229-1zbMath1432.62346OpenAlexW2061516104MaRDI QIDQ907102
Gabriel Escarela, Angelica Hernandez-Quintero, Jean-François Dupuy
Publication date: 1 February 2016
Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10463-009-0229-1
maximum likelihood estimationproportional hazards modelmixture modelcompeting riskslarge-sample propertiescensored failure time datamultinomial logistic
Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Censored data models (62N01) Reliability and life testing (62N05)
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Cites Work
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- Large sample properties of mixture models with covariates for competing risks
- An asymptotic theory for the nonparametric maximum likelihood estimator in the Cox gene model
- Modeling competing risks with a semi-parametric mixture model
- Fitting semiparametric cure models
- Maximum likelihood estimation in the proportional hazards cure model
- Consistency in a proportional hazards model incorporating a random effect
- Survival analysis. Techniques for censored and truncated data
- Asymptotic theory for the correlated gamma-frailty model
- Asymptotic theory for the frailty model
- Weak convergence and empirical processes. With applications to statistics
- Semiparametric theory and missing data.
- Asymptotic theory for the Cox model with missing time-dependent covariate
- Inference under right censoring for transformation models with a change-point based on a covariate threshold
- Estimation of the Asymptotic Variance of Semiparametric Maximum Likelihood Estimators in the Cox Model with a Missing Time-Dependent Covariate
- A SEMIPARAMETRIC MIXTURE MODEL FOR THE ANALYSIS OF COMPETING RISKS DATA
- Asymptotic Statistics
- Semi-Parametric Estimation in Failure Time Mixture Models
- Estimation in a Cox Proportional Hazards Cure Model
- Consistency of the NPML Estimator in the Right-Censored Transformation Model
- Fitting a Semi-Parametric Mixture Model for Competing Risks in Survival Data
- Maximum Likelihood Estimation in a Semiparametric Logistic/Proportional-Hazards Mixture Model
- A Semiparametric Mixture Model for Analyzing Clustered Competing Risks Data
- Semiparametric analysis of mixture regression models with competing risks data
- A mixture model combining logistic regression with proportional hazards regression
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