Random effects in promotion time cure rate models
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Cited by:
- Aurelie Bertrand & Catherine Legrand & Raymond J. Carroll & Christophe de Meester & Ingrid Van Keilegom, 2017. "Inference in a survival cure model with mismeasured covariates using a simulation-extrapolation approach," Biometrika, Biometrika Trust, vol. 104(1), pages 31-50.
- Gallardo, Diego I. & Bolfarine, Heleno & Pedroso-de-Lima, Antonio Carlos, 2016. "Destructive weighted Poisson cure rate models with bivariate random effects: Classical and Bayesian approaches," Computational Statistics & Data Analysis, Elsevier, vol. 98(C), pages 31-45.
- Gressani, Oswaldo & Lambert, Philippe, 2016. "Fast Bayesian inference in semi-parametric P-spline cure survival models using Laplace approximations," LIDAM Discussion Papers ISBA 2016041, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Bremhorst, Vincent & Kreyenfeld, Michaela & Lambert, Philippe, 2017. "Nonparametric double additive cure survival models: an application to the estimation of the nonlinear effect of age at first parenthood on fertility progression," LIDAM Discussion Papers ISBA 2017004, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Gressani, Oswaldo & Lambert, Philippe, 2018. "Fast Bayesian inference using Laplace approximations in a flexible promotion time cure model based on P-splines," Computational Statistics & Data Analysis, Elsevier, vol. 124(C), pages 151-167.
- Durga H. Kutal & Lianfen Qian, 2018. "A Non-Mixture Cure Model for Right-Censored Data with Fréchet Distribution," Stats, MDPI, vol. 1(1), pages 1-13, November.
- Philippe Lambert & Vincent Bremhorst, 2020. "Inclusion of time‐varying covariates in cure survival models with an application in fertility studies," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(1), pages 333-354, January.
- Han, Bo & Wang, Xiaoguang, 2020. "Semiparametric estimation for the non-mixture cure model in case-cohort and nested case-control studies," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
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Keywords
Long-term survivors Random effects REML Metropolis-Hastings;Statistics
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