Generalized, Linear, and Mixed Models\n\nCharles E. McCulloch (Author), Shayle R. Searle (Author), John M. Neuhaus (Author)\n\n9780470073711, Wiley\n\nHardback, published 18 July 2008\n\n432 pages\n23.9 x 16.3 x 3 cm, 0.748 kg\n\nAn accessible and self-contained introduction to statistical models-now in a modernized new edition\n Generalized, Linear, and Mixed Models, Second Edition provides an up-to-date treatment of the essential techniques for developing and applying a wide variety of statistical models. The book presents thorough and unified coverage of the theory behind generalized, linear, and mixed models and highlights their similarities and differences in various construction, application, and computational aspects.\n A clear introduction to the basic ideas of fixed effects models, random effects models, and mixed models is maintained throughout, and each chapter illustrates how these models are applicable in a wide array of contexts. In addition, a discussion of general met]