A Bayesian analysis of relative cancer survival with geoadditive models

DOI10.1177/1471082X0800800201OpenAlexW1966789954MaRDI QIDQ4970939

Erik-André Sauleau, Andrea Hennerfeind, Leonhard Held

Publication date: 8 October 2020

Published in: Statistical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1177/1471082x0800800201

zbMATH Keywords

breast cancerMCMChazard regressionGaussian Markov random fieldsrelative survivalstructuredBayesian penalized splines

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• GMRFLib
• BayesX

Cites Work

• Unnamed Item
• Unnamed Item
• Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
• Generalized structured additive regression based on Bayesian P-splines
• Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
• The Fitting of Exponential, Weibull and Extreme Value Distributions to Complex Censored Survival Data Using GLIM
• Conditional Prior Proposals in Dynamic Models
• Bayesian Measures of Model Complexity and Fit
• Gaussian Markov Random Fields
• Estimation of the Hazards Ratio in Two Grouped Samples
• A Mixed Model Approach for Geoadditive Hazard Regression
• Geoadditive Survival Models

This page was built for publication: A Bayesian analysis of relative cancer survival with geoadditive models