Selection between proportional and stratified hazards models based on expected log-likelihood
DOI10.1007/S00180-007-0079-3zbMath1198.62135OpenAlexW2024124714MaRDI QIDQ964648
Jérôme Saracco, Daniel Commenges, Bernoît Liquet
Publication date: 22 April 2010
Published in: Computational Statistics (Search for Journal in Brave)
Full work available at URL: https://www.hal.inserm.fr/inserm-00366565/file/liquet_commenges_saracco_2007.pdf
Computational methods for problems pertaining to statistics (62-08) Nonparametric regression and quantile regression (62G08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Estimation in survival analysis and censored data (62N02)
Related Items (1)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Smoothing counting process intensities by means of kernel functions
- Smoothing noisy data with spline functions: Estimating the correct degree of smoothing by the method of generalized cross-validation
- Estimating the dimension of a model
- Bootstrapping log likelihood and EIC, an extension of AIC
- Estimating the expectation of the Log-likelihood with censored data for estimator selection
- Bootstrap Choice of Estimators in Parametric and Semiparametric Families: An Extension of EIC
- Fast Computation of Fully Automated Log-Density and Log-Hazard Estimators
- A Penalized Likelihood Approach for Arbitrarily Censored and Truncated Data: Application to Age-Specific Incidence of Dementia
- Hazard Regression
- Spline-Based Tests in Survival Analysis
- Statistical models based on counting processes
This page was built for publication: Selection between proportional and stratified hazards models based on expected log-likelihood
