Linear Model Methodology
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Linear Model Methodology

Linear Model Methodology


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About the Book

Given the importance of linear models in statistical theory and experimental research, a good understanding of their fundamental principles and theory is essential. Supported by a large number of examples, Linear Model Methodology provides a strong foundation in the theory of linear models and explores the latest developments in data analysis.After

Table of Contents:
Linear Models: Some Historical Perspectives. Basic Elements of Linear Algebra. Basic Concepts in Matrix Algebra. The Multivariate Normal Distribution. Quadratic Forms in Normal Variables. Full-Rank Linear Models. Less-Than-Full-Rank Linear Models. Balanced Linear Models. The Adequacy of Satterthwaite's Approximation. Unbalanced Fixed-Effects Models. Unbalanced Random and Mixed Models. Additional Topics in Linear Models. Generalized Linear Models. Bibliography. Index.

About the Author :
Andre I. Khuri is a Professor Emeritus in the Department of Statistics at the University of Florida in Gainesville.

Review :
Is sum, this is a carefully written and reliable book that reflects the experience of the author in teaching graduate level courses on linear models. I will certainly add it to the list of reference textbooks for the graduate one-quarter course on linear model theory taught at UC Santa Cruz. --Raquel Prado, University of California-Santa Cruz The material is well chosen and well organized, and includes many results that are not found in other textbooks. ! Throughout the book, the presentation is very clear and well organized, with a focus on mathematical developments. Most results are stated with proofs, some material is based on the author's own contributions to the field. Generally, many important special cases are treated in detail, which will make the book also highly useful as a reference. There are also many worked-out examples from different subject areas to illustrate the methods. Later chapters also include some instructions on how to use the methods in SAS. Furthermore, there are lots of exercises at the end of each chapter. ! The book is very accessible and encompassing ! the book will be an excellent choice both as a text and as a reference book. --T. Mildenberger, Statistical Papers, April 2011 The material on which this book is based has been taught in a couple of courses at the University of Florida for about 20 years and the author's skills and experience in doing this are superbly represented in this fine text. ! there are numerous exercises that reinforce both the theoretical and the practical aspects of regression! This is an excellent, reliable, and comprehensive text. --International Statistical Review (2010), 78 This book provides a thorough overview which is similar to other available texts but in a very different way. The choice of topics covered, their organization and presentation are the unique features that distinguish this book. ! This book is well structured as a textbook as well as a reference with every chapter explaining the definitions, principles and methods of the subject matter illustrated by data-based examples with the details on use of SAS software, wherever possible. ! the topics that are covered in Chapters 7--12 are not generally found in a single book. ! The book would make an excellent textbook for a course on linear models at masters and graduate levels. Moreover, some parts of the book can also be a part of a course on analysis of variance. Overall, the book is a valuable reference for those involved in research and teaching in this area. --Journal of the Royal Statistical Society, Series A, 2010


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Product Details
  • ISBN-13: 9781420010442
  • Publisher: Taylor & Francis Ltd
  • Publisher Imprint: Chapman & Hall/CRC
  • Language: English
  • ISBN-10: 1420010441
  • Publisher Date: 21 Oct 2009
  • Binding: Digital (delivered electronically)


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