A joint model for hierarchical continuous and zero-inflated overdispersed count data Universiteit Hasselt KU Leuven
Many applications in public health, medical and biomedical or other studies demand modeling of two or more longitudinal outcomes jointly to get better insight in their joint evolution. In this regard, a joint model for a longitudinal continuous and a count sequence, the latter possibly overdispersed and zero-inflated, will be specified that assembles aspects coming from each one of them into one single model. Further, a subject-specific random ...