Poisson mixed models are used to analyze a wide variety of cluster count data. These models are commonly developed based on the assumption that the random effects have either the log-normal or the gamma distribution. Obtaining consistent as well as efficient estimates for the parameters involved...

An unbalanced mixed linear model with two variance components is considered, one variance component (say [sigma]12 = 0) corresponding to a random effect (treatments) and a second variance component (say [sigma]2 0) corresponding to the experimental errors. Sufficient conditions are obtained...

In view of the cumbersome and often intractable numerical integrations required for a full likelihood analysis, several suggestions have been made recently for approximate inference in generalized linear mixed models (GLMMs). Two closely related approximate methods are the penalized...

We consider the elliptical distribution of n p-dimensional random vectors X1, ..., Xn having p.d.f. of the form k(n, p) [Lambda]-n/2 g([Sigma]j=1n(Xj-[theta])' [Lambda]-1(Xj-[theta])) as a generalization of the multivariate normal distribution. Let A denote the Wishart matrix defined by , where...

Liang and Zeger introduced a class of estimating equations that gives consistent estimates of regression parameters and of their variances in the class of generalized linear models for longitudinal data. When the response variable in such models is subject to overdispersion, the oerdispersion...