A zero-modified Poisson mixed model with generalized random effect. Issue 12 (13th August 2021)

• Record Type: Journal Article
• Authors: Raquel, Gabriela C.; Conceição, Katiane S.; Prates, Marcos O.; Andrade, Marinho G.
• Is Part Of: Journal of statistical computation and simulation. Volume 91:Issue 12(2021)
• Page Start: 2457
• Page End: 2474
• Publication Date: 2021-08-13
• Subjects: Generalized log-gamma random effect -- longitudinal count data -- mixed models -- zero-inflated data -- zero-deflated data; 62-01; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5028505
• DOI: 10.1080/00949655.2021.1898612
• Languages: English
• ISSNs: 0094-9655

Abstract

Abstract : In this paper, we present an extension of the Poisson Zero-Modified model with Normal and Generalized Log-Gamma random effects. The random effect induces correlation and accommodate the intrinsic variability of each individual. The Generalized Log-Gamma effect is a generalized Normal effect and can be used in atypical situations where the Normal effect is not appropriate. In particular, the mixed Zero-Modified Poisson model allows us to deal with longitudinal count data, without requiring any previous knowledge about data characteristics, mainly to the number of zero observations (zero-inflated or zero-deflated). We consider the maximum likelihood approach to estimate the model parameters. A simulation study is presented to evaluate the estimators' performance. A real data set referring to the number of notification of infant deaths in the municipalities of the state of Bahia/Brazil is analyzed. The results revealed the Generalized Log-Gamma effect seems to be more appropriate to model this longitudinal data set.