- Hardcover: 590 pages
- Publisher: Springer; 1st ed. 1997. Corr. 2nd printing edition (Jun 16 2000)
- Language: English
- ISBN-10: 0387950273
- ISBN-13: 978-0387950273
- Product Dimensions: 24.3 x 16.3 x 3.2 cm
- Shipping Weight: 939 g
- Average Customer Review: 5.0 out of 5 stars See all reviews (1 customer review)
- Amazon Bestsellers Rank: #808,031 in Books (See Top 100 in Books)
- See Complete Table of Contents
|
||||||||||||||||||
|
||||||||||||||||||
|
||||||||||||||||||
| |||||||||||||||
Product Details |
Product Description
Review
From the reviews: MATHEMATICAL REVIEWS "This book emphasizes practice rather than mathematical rigor and the majority of the chapters are explanatory rather than research oriented. In this respect, guidance and advice on practical issues are the main focus of the text. Hence it will be of interest to applied statisticians and biomedical researchers in industry, particularly in the pharmaceutical industry, medical public health organizations, contract research organizations, and academia." "This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Over 125 illustrations are included in the book. … I do believe that the book may serve as a useful reference to a broader audience. Since practical examples are provided as well as discussion of the leading software utilization, it may also be appropriate as a textbook in an advanced undergraduate-level or a graduate-level course in an applied statistics program." (Ana Ivelisse Avil és, Technometrics, Vol. 43 (3), 2001) "A practical book with a great many examples, including worked computer code and access to the datasets. … The authors state that the book covers ‘linear mixed models for continuous outcomes’ … . The book has four main strengths: its practical bent, its emphasis on exploratory analysis, its description of tools for model checking, and its treatment of dropout and missingness … . my impression of the book was … positive. Its strong practical nature and emphasis on dropout modelling are particularly welcome … ." (Harry Southworth, ISCB Newsletter, June, 2002) "This book is devoted to linear mixed-effects models with strong emphasis on the SAS procedure. Guidance and advice on practical issues are the main focus of the text. … It is of value to applied statisticians and biomedical researchers. … I recommend this book as a reference to applied statisticians and biomedical researchers, particularly in the pharmaceutical industry, medical and public organizations." (Wang Songgui, Zentralblatt MATH, Vol. 956, 2001)
Book Description
This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance structure. Further, model diagnostics and missing data receive extensive treatment. Sensitivity analysis for incomplete data is given a prominent place. Most analyses were done with the MIXED procedure of the SAS software package, but the data analyses are presented in a software-independent fashion.
Inside This Book
(Learn More)
First Sentence
In applied sciences, one is often confronted with the collection of correlated data. Read the first page
Front Cover | Copyright | Table of Contents | Excerpt | Index
In applied sciences, one is often confronted with the collection of correlated data. Read the first page
Explore More
Concordance
Browse Sample PagesConcordance
Front Cover | Copyright | Table of Contents | Excerpt | Index
Tag this product(What's this?)Think of a tag as a keyword or label you consider is strongly related to this product.
Tags will help all customers organize and find favorite items. |
Customer Reviews
|
Share your thoughts with other customers:
|
||||||||||||||||||||||
|
Most helpful customer reviews
5.0 out of 5 stars
thorough treatment of linear mixed models,
By
This review is from: Linear Mixed Models for Longitudinal Data (Hardcover)
This book is basically an update of their 1997 mongraph. Longitudinal data are important in biostatistics and particularly in the analysis of clinical trials. There are effective methods for handling longitudinal data using linear models with covariance structures that represent the time dependence of the repeated observations. There are many subtle issues in the analysis and many who analyze longitudinal data apply incorrect linear models and are often not aware of the consequences of their decisions. The authors were motivated to provide a reference source to remedy this problem. The book presents the theory and applications and uses SAS Proc Mixed as a vehicle for presenting many of the results in a clear and understandable fashion. An important feature of the book is its emphasis on how best to deal with the problem of missing data. This is covered in chapters 14 - 16. Although SAS is emphasized throughout the book other software tools are also illustrated in Appendix A (including SPlus). SUDAAN is a package produced by the Research Triangle Institute in North Carolina that also handles longitudinal data but is overlooked by the authors. Another great book on longitudinal data analysis is Diggle, Liang and Zeger "Analysis of Longitudinal Data" published in 1994. There have been many advances since 1994 and Verbeke and Molenberghs cover a great deal of it. You can find my review of Diggle, Liang and Zeger on Amazon. An updated second edition of their book is in the works and will probably appear in 2001.
Share your thoughts with other customers: Create your own review
Most Helpful Customer Reviews on Amazon.com (beta) Amazon.com:
4.0 out of 5 stars (3 customer reviews) 26 of 27 people found the following review helpful
5.0 out of 5 stars
excellent for applications to clinical trials data with some missing data,
By Michael R. Chernick "statman31147" - Published on Amazon.com
This review is from: Linear Mixed Models for Longitudinal Data (Hardcover)
This book is basically an update of their 1997 mongraph. Longitudinal data are important in biostatistics and particularly in the analysis of clinical trials. There are effective methods for handling longitudinal data using linear models with covariance structures that represent the time dependence of the repeated observations. There are many subtle issues in the analysis and many who analyze longitudinal data apply incorrect linear models and are often not aware of the consequences of their decisions. The authors were motivated to provide a reference source to remedy this problem. The book presents the theory and applications and uses SAS Proc Mixed as a vehicle for presenting many of the results in a clear and understandable fashion. An important feature of the book is its emphasis on how best to deal with the problem of missing data. This is covered in chapters 14 - 16. Although SAS is emphasized throughout the book other software tools are also illustrated in Appendix A (including SPlus). SUDAAN is a package produced by the Research Triangle Institute in North Carolina that also handles longitudinal data but is overlooked by the authors. Another great book on longitudinal data analysis is Diggle, Liang and Zeger "Analysis of Longitudinal Data" published in 1994. There have been many advances since 1994 and Verbeke and Molenberghs cover a great deal of it. You can find my review of Diggle, Liang and Zeger on Amazon. An updated second edition of their book has now appeared and is more up-to-date. I find this book by Verbeke and Molenberghs one of the best and most innovative on this topic. Another nice addition is the new book on missing data in clinical studies by Molenberghs and Kennard. I have written an amazon trview on that one also.
6 of 8 people found the following review helpful
5.0 out of 5 stars
Excellent book,
By Savvas Papadopoulos "riskmetrica" - Published on Amazon.com
Amazon Verified Purchase(What's this?)
This review is from: Linear Mixed Models for Longitudinal Data (Hardcover)
The book covers many advanced topics of Longitudinal data with many examples and SAS programs. Congatulations to the authors for this outstanding job.Savas Papadopoulos 1 of 2 people found the following review helpful
2.0 out of 5 stars
Poor book, better books are available,
By Madan Gopal Kundu "Madan Kundu" - Published on Amazon.com
Amazon Verified Purchase(What's this?)
This review is from: Linear Mixed Models for Longitudinal Data (Paperback)
This book is too much practical, no discussion of theory at all. Should not be recommended for any graduate course. May be useful for some applied purpose, but in that case books such as Applied Longitudinal data analysis by Fitzmaurice will serve better the purpose.I don't recommend this book at all. |
|
Listmania!
Look for similar items by category
- Books > New & Used Textbooks > Sciences > Biology & Life Sciences > Biology
- Books > New & Used Textbooks > Sciences > Mathematics > Statistics
- Books > Professional & Technical > Medical > Basic Sciences > Biostatistics
- Books > Professional & Technical > Professional Science > Mathematics > Applied
- Books > Qualifying Textbooks - Fall 2007 > Education
- Books > Qualifying Textbooks - Fall 2007 > Science
- Books > Reference > Dictionaries & Thesauruses > Science
- Books > Science > Biological Sciences > Biology
- Books > Science > Mathematics > Applied > Probability & Statistics
Look for similar items by subject
Feedback
Would you like to update product info or give feedback on images?
|
