Hierarchical and multivariate regression models to fit correlated asymmetric positive continuous outcomes

• Published in: Computational statistics Vol. 37; no. 3; pp. 1435 - 1459
• Main Authors: Fabio, Lizandra C., Cysneiros, Francisco J. A., Paula, Gilberto A., Carrasco, Jalmar M. F.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.07.2022; Springer Nature B.V
• Subjects: Asymptotic properties; Dirichlet problem; Economic Theory/Quantitative Economics/Mathematical Methods; Mathematics and Statistics; Maximum likelihood estimators; Monte Carlo simulation; Normality; Original Paper; Probability and Statistics in Computer Science; Probability Theory and Stochastic Processes; Regression models; Statistical analysis; Statistical models; Statistics; Diagnostic analysis; Generalized log-gamma distribution; Misspecification of the random-effects; Extended inverted Dirichlet model; Generalized linear mixed model

In the extant literature, hierarchical models typically assume a flexible distribution for the random-effects. The random-effects approach has been used in the inferential procedure of the generalized linear mixed models . In this paper, we propose a random intercept gamma mixed model to fit correla...