Generalized Linear Models and Extensions, Third Edition James W. Hardin Author
by James W. Hardin 2021-04-07 05:29:35
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This book presents a thorough examination of generalized linear model (GLM) estimation methods as well as the derivation of all major GLM families. Examined families include Gaussian, gamma, inverse Gaussian, binomial, Poisson, geometric, and negativ... Read more
This book presents a thorough examination of generalized linear model (GLM) estimation methods as well as the derivation of all major GLM families. Examined families include Gaussian, gamma, inverse Gaussian, binomial, Poisson, geometric, and negative binomial. The text also contains various models that have been developed on the basis of GLM theory, including GAM, ordered binomial models, multinomial logit and probit models, GEE and other quasi-likelihood models, fixed and random effects models, and random intercept and random parameter models. Using Stata, the book offers numerous examples to assist you in applying the models to your own data situations. Less
  • File size
  • Print pages
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  • Publication date
  • ISBN
  • 7.20(w)x9.30(h)x1.10(d)
  • 479
  • Stata Press
  • June 4, 2012
  • 9781597181051
James W. Hardin is the Division Director of Biostatistics and an associate professor in the Department of Epidemiology and Biostatistics at the University of South Carolina. He is also an affiliated f...
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