Statistical Modelling 22 (1&2) (2022), 46–66
Random effect models for multivariate mixed data: A Parafac-based finite mixture approach
Marco Alfò
Dipartimento di Scienze Statistiche,
Sapienza Università di Roma,
Rome,
Italy.
e-mail: marco.alfo@uniroma1.it
Paolo Giordani,
Dipartimento di Scienze Statistiche,
Sapienza Università di Roma,
Rome,
Italy.
Abstract:
We discuss a flexible regression model for multivariate mixed responses. Dependence between outcomes is introduced via the joint distribution of discrete outcome- and individual-specific random effects that represent potential unobserved heterogeneity in each outcome profile. A different number of locations can be used for each margin, and the association structure is described by a tensor that can be further simplified by using the Parafac model. A case study illustrates the proposal.
Keywords:
multivariate mixed responses, finite mixtures, random effects, tensor analysis, Parafac
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