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Hagenaars and Allan L. Bollen and Patrick J. Preacher, Aaron L. Wichman, Robert C. MacCallum and Nancy E. McLachlan and D. Waller and Paul E. Hosmer, Jr. Andries van der Ark, Marcel A. Johnson and James H. Singer and John B. Fitzmaurice, Nan M. Laird and James H. Little, James A. Bovaird and Noel A. Repository Staff Only: item control page. QUT Home Contact. Home Browse About. Description Introduces GLMs in a way that enables readers to understand the unifying structure that underpins them.
Continuing to emphasize numerical and graphical methods, An Introduction to Generalized Linear Models, Third Edition provides a cohesive framework for statistical modeling.
Like its predecessor, this edition presents the theoretical background of generalized linear models GLMs before focusing on methods for analyzing particular kinds of data. It covers normal, Poisson, and binomial distributions; linear regression models; classical estimation and model fitting methods; and frequentist methods of statistical inference.
After forming this foundation, the authors explore multiple linear regression, analysis of variance ANOVA , logistic regression, log-linear models, survival analysis, multilevel modeling, Bayesian models, and Markov chain Monte Carlo MCMC methods. Using popular statistical software programs, this concise and accessible text illustrates practical approaches to estimation, model fitting, and model comparisons.
It includes examples and exercises with complete data sets for nearly all the models covered. Impact and interest: citations in Scopus.
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