Advanced Bayesian survival analysis with merlin and morgana

In this talk I will describe our latest work to bring advanced Bayesian survival analysis tools to Stata. Previously, we have introduced the morgana prefix command (bayesmh in disguise), which provides a Bayesian wrapper for survival models fitted with stmerlin (which is merlin’s more user friendly wrapper designed for working with st data). We have now begun the work to sync morgana with the much more general merlin command, to allow for Bayesian multiple outcome models. Within survival analysis, multiple outcomes arise when we consider competing risks or the more general setting of multi-state processes. Using an example in breast cancer, I will show how to estimate competing risks and illness- death multi-state models within a Bayesian framework, incorporating prior information for covariate effects, and baseline hazard parameters. Importantly, we have also developed the predict functionality to obtain a wide range of easily interpretable predictions, such as cumulative incidence functions and (restricted) life-expectancy, along with their credible intervals.