摘要： Longitudinal data are often collected in medical and biomedical applications where measurements on more than one response can be taken from a given subject repeatedly overtime. For some problems, these multivariate profiles need to be modeled jointly in order to get insight on the joint evolution and/or association of these responses over time. In practice, these multiple longitudinal outcomes may have zeros, that need to be accounted for in the analysis. For example, in dietary intake studies, as we focus on in this paper, some food components are eaten daily by almost all subjects, while others are consumed episodically, where individuals have time periods where they do not eat these components followed by periods where they do. These episodically consumed foods need to be carefully modeled to account for the many zeros that are encountered. In this paper, we propose a multivariate zero-inflated joint model to analyze multivariate hierarchical semicontinuous data characterized by excess zeros and more than one replicate observations at each measurement occasion. This approach allows for different probability mechanisms for describing the zero behavior as compared with the mean intake given that the individual consumes the food. To deal with the potentially large number of multivariate profiles, we use a pairwise model fitting approach that was developed in the context of multivariate Gaussian random effects models with large number of multivariate components. The novelty of the proposed approach is that it assembles aspects coming from: (1) multivariate, possibly correlated, response variables; (2) within subject correlation resulting from repeated measurements taken from each subject; (3) excess zero observations; (5) overdispersion; and (6) replicate measurement effects at each visit time. We illustrate our method with analyses from a recent dietary study setup to evaluate the efficacy of a family based behavioral intervention that integrated motivational interviewing, active learning, and applied problem-solving to increase intake of whole plant foods (fruits, vegetables, whole grains, legumes, nuts and seeds) among youth with type 1 diabetes.