… reviews several semiparametric Bayesian survival models, and summarizes some recent
proposals to allow for spatial and covariate-adjusted dependence among the survival times. …

… I apply the Bayesian spatial survival modeling approach to the timing … I find that spatial shared
frailty models outperform standard … Next, I examine the Bayesian spatial survival modeling …

… survival. This paper provides an introduction to a set of programs for implementing some
Bayesian spatial survival models … commonly-used semiparametric models: proportional hazards…

… walk-through analysis of a spatial survival dataset in the R programming language. … to
survival models, spatial survival models, the form of the likelihood function and Bayesian statistical …

… may be useful to include spatial information in the survival model. Bayesian spatial survival
models have recently emerged in the literature, and commonly spatially structured priors are …

… and Bayesian spatial survival models on the same cohort. … -time and Bayesian spatial
survival models to a population-… and Bayesian spatial survival models used in this case study …

… basic model with respect to several aspects. We propose novel nonparametric Bayesian
survival models that … into groups x, z, and v and adding a spatial index s , we extend model (1) to …

… and a semiparametric Cox proportional hazards model. In this study, a Bayesian spatial
survival method via a CAR approach was used to analyze DF patients’ survival, and to …

… ) estimation routines for SP survival models with independent (… work on SP and spatial
survival models, including existing … , and Spatial Bayesian SP survival models before describing …

… effect of survival model to … survival model is implemented using Markov Chain Monte
Carlo (MCMC) method with Gibbs sampling3, 4. Darmofal3 implemented spatial survival model …