Article ID Journal Published Year Pages File Type
415301 Computational Statistics & Data Analysis 2008 13 Pages PDF
Abstract

Normality of random effects and error terms is a routine assumption for linear mixed models. However, such an assumption may be unrealistic, obscuring important features of within- and among-unit variation. A simple and robust Bayesian parametric approach that relaxes this assumption by using a multivariate skew-elliptical distribution, which includes the Skew-tt, Skew-normal, tt-Student, and Normal distributions as special cases and provides flexibility in capturing a broad range of non-normal and asymmetric behavior is presented. An appropriate posterior simulation scheme is developed and the methods are illustrated with an application to a longitudinal data example.

Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics
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