The mixed model for the analysis of a repeated-measurement multivariate count data.

ABSTRACT: Clustered overdispersed multivariate count data are challenging to model due to the presence of correlation within and between samples. Typically, the first source of correlation needs to be addressed but its quantification is of less interest. Here, we focus on the correlation between time points. In addition, the effects of covariates on the multivariate counts distribution need to be assessed. To fulfill these requirements, a regression model based on the Dirichlet-multinomial distribution for association between covariates and the categorical counts is extended by using random effects to deal with the additional clustering. This model is the Dirichlet-multinomial mixed regression model. Alternatively, a negative binomial regression mixed model can be deployed where the corresponding li

SUBMITTER: Martin I 

PROVIDER: S-EPMC6594162 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature