Longitudinal Data Analysis (Chapman & Hall/CRC Handbooks of Modern Statistical Methods) [Hardcover]

Garrett Fitzmaurice (Editor), Marie Davidian (Editor), Geert Verbeke (Editor), Geert Molenberghs (Editor)

Book Description

ISBN-10: 1584886587 | ISBN-13: 978-1584886587 | Publication Date: August 11, 2008 | Edition: 1

Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature. Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory and applications. It also focuses on the assorted challenges that arise in analyzing longitudinal data.

After discussing historical aspects, leading researchers explore four broad themes: parametric modeling, nonparametric and semiparametric methods, joint models, and incomplete data. Each of these sections begins with an introductory chapter that provides useful background material and a broad outline to set the stage for subsequent chapters. Rather than focus on a narrowly defined topic, chapters integrate important research discussions from the statistical literature. They seamlessly blend theory with applications and include examples and case studies from various disciplines.

Destined to become a landmark publication in the field, this carefully edited collection emphasizes statistical models and methods likely to endure in the future. Whether involved in the development of statistical methodology or the analysis of longitudinal data, readers will gain new perspectives on the field.

Editorial Reviews

Review

The scope is remarkable, and the degree of integration and polish is admirable. The contributors include many of the most innovative researchers in the field, and happily, many of the clearest writers as well. … a lively text with clear-eyed positions and well-argued recommendations on how to analyze data of specific structures. … [material] is all accessible, well explained, and well illustrated using examples … a very good book … an excellent resource for a graduate class for statisticians or biostatisticians, and as a reference for quantitatively minded researchers.
—Statistics in Medicine, 2011

The volume’s editors have assembled a world-class panel of contributors; many have made seminal contributions to the field (this includes the editors themselves). Immediately apparent is the uniformity of notation and writing style not typically found in volumes of this kind. The editors clearly have taken great care to ensure a whole document rather than a disjointed patchwork typical of similar collections. Chapters reflect contributor diversity while suppressing distracting idiosyncrasies. … Experienced researchers and those new to the field will find useful material here. … several chapters provide fresh insights. For graduate students and new researchers, the book provides a useful introduction and comprehensive reference material for the topics it covers. Case studies and software enable readers to implement some methods described in the book, with supplemental datasets and programs appearing on a useful website. … A strong inaugural volume for Chapman & Hall’s new series on modern statistical methods, Longitudinal Data Analysis provides an outstanding model for future entries.
—Biometrics, September 2010

… Longitudinal Data Analysis is the first book to collect and sort through many of the most important developments. The authors make clear the assumptions of the statistical methods and their consequences. Coupled with an abundance of examples, the book guides the practitioner about when to apply one method as opposed to another. The book has remarkable breadth and contains material that would likely be new even to those that analyze longitudinal data on a regular basis. Longitudinal Data Analysis would be useful for applied statisticians looking to expand their analytical toolkit and statistical researchers familiar with the area but looking for a good reference. …an excellent text for a special topics course for Ph.D. students in statistics. It has a good balance of statistical theory and applications, with a large number of real data examples and case studies to illustrate how to use the methods described therein. …a well organized, excellent overview of the state of the art in modeling longitudinal data and would make a useful supplement to the library of anyone that analyzes this type of data.
—Journal of the American Statistical Association, June 2010

…a concise but complete encyclopedia on longitudinal data analysis. The editors have made a great effort to produce a volume providing a comprehensive and up-to-date view of the theory and application of longitudinal data analysis. … One of the strengths of the book is the organizational structure and the fact that the book has been written by well-known experts in the field. … I find this book very useful for statisticians and researchers in many fields where the interest relies on studying the change of an outcome or multiple outcomes over time. Many of the chapters include examples and case studies in different disciplines and some of this material can be found in the website of this book (http://www.biostat.harvard.edu/ fitzmaur/lda). I would like to congratulate the editors and all the contributing authors for preparing this comprehensive handbook on many interesting and complementary aspects of the theory and applications of longitudinal data analysis. This handbook will have, without any doubt, an important place on the shelf of those statisticians and applied researchers working with longitudinal data.
—Journal of Applied Statistics, Vo. 36, No. 10, October 2009

This is public-service broadcasting at its best. Many of the leading internationally recognized experts in the field have been assembled to write a series of expository articles on an important area of modern statistics. … Care has clearly been taken to make the book hang together—it’s not like some ‘edited tomes’ consisting of a set of papers stapled together. There is a mixture of theory and applications with real data, some of which is available on a website. In my opinion the book will be a must-have for anyone seriously involved with repeated measures or longitudinal data.
—International Statistical Review, 2009

Other longitudinal data books do not have the breadth of this one. … I highly recommend this book to anyone interested in learning about modern methods for longitudinal data analysis. I think it would make a particularly good book for a Ph.D.-level reading course or as a supplement to a longitudinal data textbook in a graduate-level course. I especially recommend this book to statistical researchers, as it makes a great reference book.
—Journal of Biopharmaceutical Statistics, Issue 4, 2009

About the Author

Harvard School of Public Health, Boston, MA, USA North Carolina State University, Raleigh, USA Leuven University, Belgium Hasselt University, Diepenbeek, Belgium

Product Details

• Hardcover: 632 pages
• Publisher: Chapman and Hall/CRC; 1 edition (August 11, 2008)
• Language: English
• ISBN-10: 1584886587
• ISBN-13: 978-1584886587
• Product Dimensions: 10.1 x 7 x 1.3 inches
• Shipping Weight: 2.8 pounds (View shipping rates and policies)
• Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
• Amazon Best Sellers Rank: #238,953 in Books (See Top 100 in Books)

Customer Reviews

Most Helpful Customer Reviews

2 of 2 people found the following review helpful:

5.0 out of 5 stars Your travel guide to the world of longitudinal data, October 21, 2010

By 

M. Wierzbicki "In quotes" (Philly) - See all my reviews
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This review is from: Longitudinal Data Analysis (Chapman & Hall/CRC Handbooks of Modern Statistical Methods) (Hardcover)

First of all, this isn't really a textbook. It's more of an encyclopedia-textbook hybrid. You won't find proofs of theorems or (many) fully worked examples, however you'll get thorough descriptions of methods, their current status and their full history. Each section is written by one to four of the 32 contributors of the text, with each contributor writing on his/her expertise. Contributors include: Fitzmaurice, Verbeke, Molenberghs, Brumback, Carroll, Diggle, Little, Muller, Robins, among others.

If a section is not thorough enough for your liking, the authors refer you to a plethora of relevant papers for just about everything that is stated in the text. This makes it incredibly easy to investigate further into a given topic. Furthermore, the references are fairly current, with some sections including references up to the year 2007.

As I eluded to before, not only does each chapter cover different methodologies for analyzing longitudinal data, but also includes a history of research regarding a method -- what we used before those methods were introduced, why they were lacking, how the current methods address some of those problems, and what directions exist for further research. This gives the reader a picture of how the field has evolved and adapted to problems that longitudinal data analyses presents researchers. Some may find this uninteresting, but to see the historical research process for some of these methods, in my opinion, illustrates how the field has reached the point it is today and more generally, how research progresses in the real world.

The non-parametric/semi-parametric regression methods and missing data sections are especially appealing for I am unaware of any other source which compiles all current research in these areas in one volume.

As I say in the title of my review, this is akin to a 'travel-guide.' For example you won't find a derivation of GEE in this text, but you'll find what they are, why they were introduced, what they replaced, why we bother using them, what properties they have, what extensions researchers have come up with, and what we still don't know...and most importantly, you'll be directed to where you can find the derivations of all of these. Thus it won't be your final stop in researching any methodology for longitudinal data, but it most likely turn into your first.

This text is a great picture of what can be done with this series of texts (Handbooks of Modern Statistical Methods). I look forward to future installments.