Generalized, Linear, and Mixed Models

Beschreibung

Wiley Series in Probability and Statistics A modern perspective on mixed models The availability of powerful computing methods in recent decadeshas thrust linear and nonlinear mixed models into the mainstream ofstatistical application. This volume offers a modern perspective ongeneralized, linear, and mixed models, presenting a unified andaccessible treatment of the newest statistical methods foranalyzing correlated, nonnormally distributed data. As a follow-up to Searle's classic, Linear Models, and VarianceComponents by Searle, Casella, and McCulloch, this new workprogresses from the basic one-way classification to generalizedlinear mixed models. A variety of statistical methods are explainedand illustrated, with an emphasis on maximum likelihood andrestricted maximum likelihood. An invaluable resource for appliedstatisticians and industrial practitioners, as well as studentsinterested in the latest results, Generalized, Linear, and MixedModels features: * A review of the basics of linear models and linear mixedmodels * Descriptions of models for nonnormal data, including generalizedlinear and nonlinear models * Analysis and illustration of techniques for a variety of realdata sets * Information on the accommodation of longitudinal data using thesemodels * Coverage of the prediction of realized values of randomeffects * A discussion of the impact of computing issues on mixed models

Autor*in

Charles E. McCulloch

Themen in »Generalized, Linear, and Mixed Models«

Angew. Wahrscheinlichkeitsrechn. u. Statistik / Modelle Applied Probability & Statistics - Models Mathematik / Wahrscheinlichkeitstheorie, Statistik Statistics Statistik Statistische Analyse Verallgemeinertes lineares Modell

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"I strongly recommend.[it] for inclusion in math andstatistics libraries and in the personal libraries of professionalstatisticians." (Journal of the American StatisticalAssociation, December 2006) ".well written and suitable to be a textbook.Ienjoyed reading this book and recommend it highly tostatisticians." (Journal of Statistical Computation andSimulation, January 2006) "This text is to be highly recommended as one that provides amodern perspective on fitting models to data." (Short BookReviews, Vol. 21, No. 2, August 2001) "For graduate students and?statisticians, McCulloch and Searlebegin by reviewing the basics of linear models and linear mixedmodels." (SciTech Book News, Vol. 25, No. 4, December2001) ".a very good reference book." (Zentralblatt MATH, Vol.964, 2001/14) ".another fine contribution to the statistics literature fromthese respected authors." (Technometrics, Vol. 45, No. 1,February 2003)
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