Event History Data
Event History Data
This chapter extends Bayesian approaches for smoothing and regression developed in previous chapters to regression models for survival and event history data with structured additive predictors. This allows for the inclusion of nonlinear time-varying effects and flexible covariate effects, spatial effects, and random effects in addition to common linear predictors and to estimate them simultaneously based on full or empirical Bayes inference. Alternative approaches and other model types are outlined in Section 6.6.
Keywords: Bayesian smoothing, regression models, survival data, survival analysis, Bayes inference, continuous-time hazard regression, discrete-time hazard regression, accelerated failure time models
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