The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 24, No. 2 (Jun., 1996), pp. 177-192 (16 pages) Liang and Zeger (1986) introduced a class of estimating equations that ...
Generalized linear mixed models (GLMM) are useful in a variety of applications. With surrogate covariate data, existing methods of inference for GLMM are usually computationally intensive. We propose ...
In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...
Many response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, modeling the state damaged/not damaged of cells after treated with ...
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