Estimation in Generalized Linear Models with Random Effects
提出一种简单通用的算法，用于估计含随机效应的广义线性模型中的固定效应、随机效应和离散成分，并应用于两个数据集说明离散成分估计和过度离散建模。
A conceptually very simple but general algorithm for the estimation of the fixed effects, random effects, and components of dispersion in generalized linear models with random effects is proposed. Conditions are described under which the algorithm yields approximate maximum likelihood or quasi-maximum likelihood estimates of the fixed effects and dispersion components, and approximate empirical Bayes estimates of the random effects. The algorithm is applied to two data sets to illustrate the estimation of components of dispersion and the modelling of overdispersion.