Competing risks joint models using R-INLA

The methodological advancements made in the field of joint models are numerous. None less, case competing risks has largely been neglected, especially from a practitioner's point view. In relevant works on models, assumptions Gaussian linear longitudinal series and proportional cause-specific hazard functions, amongst others, have remained unchallenged. this article, we provide framework based R-INLA to apply unifying way such that non-Gaussian data, spatial structures, times-dependent splines various latent association mention few, all embraced our approach. Our motivation stems SANAD trial which exhibits non-linear trajectories for failure treatment. We also present discrete model count data as well specific examples.