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A joint model for hierarchical continuous and zero-inflated overdispersed count data
2013
Journal of Statistical Computation and Simulation
Many applications in public health, medical and biomedical or other studies demand modelling of two or more longitudinal outcomes jointly to get better insight into their joint evolution. In this regard, a joint model for a longitudinal continuous and a count sequence, the latter possibly overdispersed and zero-inflated (ZI), will be specified that assembles aspects coming from each one of them into one single model. Further, a subject-specific random effect is included to account for the
doi:10.1080/00949655.2013.829058
fatcat:xbs2akoazrekxcww2p52uvqnty