A Nonparametric Frailty Model for Clustered Survival Data
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Publication:3007834
DOI10.1080/03610920903480882zbMath1215.62034OpenAlexW2093652853MaRDI QIDQ3007834
Publication date: 17 June 2011
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610920903480882
Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05) Bayesian inference (62F15) Estimation in survival analysis and censored data (62N02)
Related Items (3)
Flexible Modeling of Frailty Effects in Clustered Survival Data ⋮ Detecting influential data in multivariate survival models ⋮ A novel outlier statistic in multivariate survival models and its application to identify unusual under-five mortality sub-districts in Malawi
Uses Software
Cites Work
- Unnamed Item
- Modelling Heterogeneity With and Without the Dirichlet Process
- Cox's regression model for counting processes: A large sample study
- Markov chains for exploring posterior distributions. (With discussion)
- A Bayesian analysis of some nonparametric problems
- Hierarchical likelihood approach for frailty models
- Bayesian Nonparametric Modeling Using Mixtures of Triangular Distributions
- Hierarchical Dirichlet Processes
- A Semiparametric Multilevel Survival Model
- Semiparametric analysis of clustered survival data under nonparametric frailty
- Nonparametric Maximum Likelihood Estimation of a Mixing Distribution
- Estimating Normal Means with a Dirichlet Process Prior
- A Nested Frailty Model for Survival Data, With an Application to the Study of Child Survival in Northeast Brazil
- A Semiparametric Bayesian Approach to the Random Effects Model
- A General Framework for Random Effects Survival Analysis in the Cox Proportional Hazards Setting
- Gibbs Sampling Methods for Stick-Breaking Priors
- A Semiparametric Mixture Model for Analyzing Clustered Competing Risks Data
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