Overview
The linear mixed model has become the main parametric tool for the analysis of continuous longitudinal data, as the authors discussed in their 2000 book. Without putting too much emphasis on software, the book shows how the different approaches can be implemented within the SAS software package. The authors received the American Statistical Association's Excellence in Continuing Education Award based on short courses on longitudinal and incomplete data at the Joint Statistical Meetings of 2002 and 2004.
Full Product Details
Author: Geert Molenberghs ,
Geert Verbeke
Publisher: Springer-Verlag New York Inc.
Imprint: Springer-Verlag New York Inc.
Edition: 1st ed. Softcover of orig. ed. 2005
Dimensions:
Width: 15.50cm
, Height: 3.60cm
, Length: 23.50cm
Weight: 1.074kg
ISBN: 9781441920430
ISBN 10: 1441920439
Pages: 687
Publication Date: 01 December 2010
Audience:
Professional and scholarly
,
Professional & Vocational
Format: Paperback
Publisher's Status: Active
Availability: In Print
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Reviews
From the reviews: Strengths of this book include its breadth of topics, excellent organization and clarity of writing...I highly recommend this book to my colleagues and students. -Justine Shults for the Journal of Biopharmaceutical Statistics, Issue 3, 2006 Models for Discrete Longitudinal Data is an excellent choice for any statistician with an interest in analyzing discrete longitudinal data. It covers all of the theoretical and applied aspects in this area and is organized in such a way to serve as a handy reference guide for applied statisticians, especially those in biomedical fields. I learned a great deal from this book, and I recommend it highly to others. -John Williamson for the Journal of the American Statistical Association, September 2006 This book complements Verbeke and Molenberghs (2000), which focused on models based on the multivariate normal distribution. ... This book covers the alternative models and approaches in a methodical and accessible manner. The emphasis in the book is on presenting methods for solving practical problems, and the authors succeed admirably in this. ... The material is clearly presented ... . This book is very welcome, and will undoubtedly prove to be useful and influential. (B. J. T. Morgan, Short Book Reviews, Vol. 26 (2), 2006) This book provides a comprehensive treatment of modeling approaches for non-Gaussian repeated measures ... . the book shows how the different approaches can be implemented within the SAS software package. The text is so organized that the reader can skip the software-oriented chapters and sections without breaking the logical flow. ... It is a very important, modern and useful book for statisticians. (T. Postelnicu, Zentralblatt MATH, Vol. 1093 (19), 2006) This book ... concentrates on models for non-normally distributed longitudinal data, like binary or categorical data. ... The book under review is a comprehensive collection of latest models for non-normally distributed longitudinal data. ... Models for Discrete Longitudinal Data addresses interested (and experienced) students and lectures as well as practitioners looking for solutions of everyday problems. (K. Webel, Advances in Statistical Analysis, Vol. 91 (2), 2007)
From the reviews: Strengths of this book include its breadth of topics, excellent organization and clarity of writing...I highly recommend this book to my colleagues and students. -Justine Shults for the Journal of Biopharmaceutical Statistics, Issue 3, 2006 Models for Discrete Longitudinal Data is an excellent choice for any statistician with an interest in analyzing discrete longitudinal data. It covers all of the theoretical and applied aspects in this area and is organized in such a way to serve as a handy reference guide for applied statisticians, especially those in biomedical fields. I learned a great deal from this book, and I recommend it highly to others. -John Williamson for the Journal of the American Statistical Association, September 2006 This book complements Verbeke and Molenberghs (2000), which focused on models based on the multivariate normal distribution. ! This book covers the alternative models and approaches in a methodical and accessible manner. The emphasis in the book is on presenting methods for solving practical problems, and the authors succeed admirably in this. ! The material is clearly presented ! . This book is very welcome, and will undoubtedly prove to be useful and influential. (B. J. T. Morgan, Short Book Reviews, Vol. 26 (2), 2006) This book provides a comprehensive treatment of modeling approaches for non-Gaussian repeated measures ! . the book shows how the different approaches can be implemented within the SAS software package. The text is so organized that the reader can skip the software-oriented chapters and sections without breaking the logical flow. ! It is a very important, modern and useful book for statisticians. (T. Postelnicu, Zentralblatt MATH, Vol. 1093 (19), 2006) This book ! concentrates on models for non-normally distributed longitudinal data, like binary or categorical data. ! The book under review is a comprehensive collection of latest models for non-normally distributed longitudinal data. ! Models for Discrete Longitudinal Data addresses interested (and experienced) students and lectures as well as practitioners looking for solutions of everyday problems. (K. Webel, Advances in Statistical Analysis, Vol. 91 (2), 2007)
From the reviews: Strengths of this book include its breadth of topics, excellent organization and clarity of writing...I highly recommend this book to my colleagues and students. -Justine Shults for the Journal of Biopharmaceutical Statistics, Issue 3, 2006 Models for Discrete Longitudinal Data is an excellent choice for any statistician with an interest in analyzing discrete longitudinal data. It covers all of the theoretical and applied aspects in this area and is organized in such a way to serve as a handy reference guide for applied statisticians, especially those in biomedical fields. I learned a great deal from this book, and I recommend it highly to others. -John Williamson for the Journal of the American Statistical Association, September 2006 This book complements Verbeke and Molenberghs (2000), which focused on models based on the multivariate normal distribution. ... This book covers the alternative models and approaches in a methodical and accessible manner. The emphasis in the book is on presenting methods for solving practical problems, and the authors succeed admirably in this. ... The material is clearly presented ... . This book is very welcome, and will undoubtedly prove to be useful and influential. (B. J. T. Morgan, Short Book Reviews, Vol. 26 (2), 2006) This book provides a comprehensive treatment of modeling approaches for non-Gaussian repeated measures ... . the book shows how the different approaches can be implemented within the SAS software package. The text is so organized that the reader can skip the software-oriented chapters and sections without breaking the logical flow. ... It is a very important, modern and useful book for statisticians. (T. Postelnicu, Zentralblatt MATH, Vol. 1093 (19), 2006) This book ... concentrates on models for non-normally distributed longitudinal data, like binary or categorical data. ... The book under review is a comprehensive collection of latest models for non-normally distributed longitudinal data. ... Models for Discrete Longitudinal Data addresses interested (and experienced) students and lectures as well as practitioners looking for solutions of everyday problems. (K. Webel, Advances in Statistical Analysis, Vol. 91 (2), 2007)
