A flexible joint modeling framework for longitudinal and time-to-event data with overdispersion
A flexible joint modeling framework for longitudinal and time-to-event data with overdispersion
We combine conjugate and normal random effects in a joint model for outcomes, at least one of which is non-Gaussian, with particular emphasis on cases in which one of the outcomes is of survival type. Conjugate random effects are used to relax the often-restrictive mean-variance prescription in the non-Gaussian outcome, …