The paper proposes a multivariate mixed-effects model based on correlated random effects for jointly modeling multiple outcomes recorded on units clustered within small areas. This approach captures the multivariate dependence among outcomes through latent terms in the model. The proposed method is evaluated through an extensive simulation study that considers various types of outcomes.
Small area estimation via multivariate generalized linear mixed effects models / Emilia Rocco; Maria Francesca Marino. - ELETTRONICO. - (2021), pp. 106-111. (Intervento presentato al convegno SAE2021: Conference on Big Data for Small Area Estimation - BIG4small (SAE2021 - www.sae2021.org) - a Satellite Meeting of the International Statistical Institute 63rd World Statistics tenutosi a Università degli Studi di Napoli Federico II - Convegno on-line nel September 20-24, 2021).
Small area estimation via multivariate generalized linear mixed effects models
Emilia Rocco;Maria Francesca Marino
2021
Abstract
The paper proposes a multivariate mixed-effects model based on correlated random effects for jointly modeling multiple outcomes recorded on units clustered within small areas. This approach captures the multivariate dependence among outcomes through latent terms in the model. The proposed method is evaluated through an extensive simulation study that considers various types of outcomes.
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