Overdispersion Models in SAS
Overdispersion Models in SAS provides a friendly methodology-based introduction to the ubiquitous phenomenon of overdispersion. A basic yet rigorous introduction to the several different overdispersion models, an effective omnibus test for model adequacy, and fully functioning commented SAS codes are given for numerous examples. The examples, many of which use the GLIMMIX, GENMOD, and NLMIXED procedures, cover a variety of fields of application, including pharmaceutical, health care, and consumer products. The book is ideal as a textbook for an M.S.-level introductory course on estimation methods for overdispersion and generalized linear models as well as a first reading for students interested in pursuing this fertile area of research for further study. Topics covered include quasi-likelihood models; likelihood overdispersion binomial, Poisson, and multinomial models; generalized overdispersion linear models (GLOM); goodness-of-fit for overdispersion binomial models; Kappa statistics; marginal and conditional models; generalized estimating equations (GEE); ratio estimation; small sample bias correction of GEE; generalized linear mixed models (GLMM); and generalized linear overdispersion mixed models (GLOMM).
This book is part of the SAS Press program.
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Chapter 2 Generalized Linear Models
Chapter 3 Quasilikelihood Functions
Chapter 4 Likelihood Models for Overdispersed Binomial Responses
Chapter 5 Goodnessoffit Tests for Overdispersed Binomial Models
Chapter 6 Likelihood Models for Overdispersed Count Responses
Chapter 7 Likelihood Models for Overdispersed Multinomial Responses
Chapter 8 A Twostage Maximum Likelihood Estimation Procedure