A Mixed Model Approach for Geoadditive Hazard Regression

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Propriety of posteriors in structured additive regression models: Theory and empirical evidence (2009, methodology): “…throughout recent years and has been used to estimate semiparametric regression models in a variety of settings (compare Ruppert et al. (2003) for an overview, Fahrmeir et al. (2004) for results on exponential family STAR models, and Kneib & Fahrmeir (2007) for mixed model based hazard regression).”
A Unified Framework for Fitting Bayesian Semiparametric Models to Arbitrarily Censored Survival Data, Including Spatially Referenced Data (2017, methodology): “Note that Kneib and Fahrmeir (2007) simply fixed φ at φ0, while we allow φ to be random around φ0.”
Bayesian semi parametric multi-state models (2008, methodology): “Both inferential procedures borrow from approaches that have been recently developed for continuous time survival models (compare Kneib and Fahrmeir (2007) for the empirical Bayes version and Hennerfeind et al. (2006) for the fully Bayesian approach) and extend them to the more general setup of…”
An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach (2011, methodology): “Kneib and Fahrmeir (2007) reanalysed the same data-set using a Cox proportional hazards model but, for computational reasons, used a low-rank approximation for the spatial component.”