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Generalized Linear Mixed Models: An Application, Stephen D. Kachman, Walter W. Stroup
Generalized Linear Mixed Models: An Application, Stephen D. Kachman, Walter W. Stroup
Conference on Applied Statistics in Agriculture
The purpose of this paper is to present a specific application of the generalized linear mixed model. Often of interest to animal-breeders is the estimation of genetic parameters associated with certain traits. When the trait is measured in terms of a normally distributed response variable, standard variance-component estimation and mixed-model procedures can be used. Increasingly, breeders are interested in categorical traits (degree of calving difficulty, number born, etc.). An application of the generalized linear mixed to an animal breeding study of the number of lambs born alive will be presented. We will show how the model is determined, how the …
Generalized Linear Mixed Models - An Overview, W. W. Stroup, S. D. Kachman
Generalized Linear Mixed Models - An Overview, W. W. Stroup, S. D. Kachman
Conference on Applied Statistics in Agriculture
Generalized linear models provide a methodology for doing regression and ANOV A-type analysis with data whose errors are not necessarily normally-distributed. Common applications in agriculture include categorical data, survival analysis, bioassay, etc. Most of the literature and most of the available computing software for generalized linear models applies to cases in which all model effects are fixed. However, many agricultural research applications lead to mixed or random effects models: split-plot experiments, animal- and plant-breeding studies, multi-location studies, etc. Recently, through a variety of efforts in a number of contexts, a general framework for generalized linear models with random effects, the …