Methods for Meta-Analysis in Medical Research (Wiley Series in Probability and Statistics - Applied Probability and Statistics Section) (Hardcover)

by Alexander J Sutton (Author), Keith R. Abrams (Author), David R Jones (Author), Trevor A. Sheldon (Author), Fujian Song (Author) "There has been a growing international interest in the development of measures to help ensure that public policy and practice decision making is better informed..." (more)
Key Phrases: standard random effects model, multiple outcome model, pooled log odds ratio, New York, Russell Sage Foundation, The Handbook of Research Synthesis (more...)

Editorial Reviews

Review
"This well-written book offers an exhaustive criticism and up-to-date references, illustrates effectively with real life examples and data…" (Journal of Statistical Computation & Simulation, July 2004)

"this is an excellent book..." (Short Book Reviews, April 2001)

"...recommended for mathematically skilled readers interested in getting an overview of the various methods and the existing literature..." (Statistics in Medicine, 15 October 2003) 

Product Description
With meta-analysis methods playing a crucial role in health research in recent years, this important and clearly-written book provides a much-needed survey of the field.
Meta-analysis provides a framework for combining the results of several clinical trials and drawing inferences about the effectiveness of medical treatments. The move towards evidence-based health care and practice is underpinned by the use of meta-analysis. This book:
* Provides a thorough criticism and an up-to-date survey of meta-analysis methods
* Emphasises the practical approach, and illustrates the methods by numerous examples
* Describes the use of Bayesian methods in meta-analysis
* Includes discussion of appropriate software for each analysis
* Includes numerous references to more advanced treatment of specialist topics
* Refers to software code used in the examples available on the authors' Web site
Practising statisticians, statistically-minded clinicians and health research professionals will benefit greatly from the clear presentation and numerous examples. Medical researchers will grasp the basic principles of meta-analysis, and learn how to apply the various methods.

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Product Details

• Hardcover: 346 pages
• Publisher: Wiley; 1 edition (December 27, 2000)
• Language: English
• ISBN-10: 0471490660
• ISBN-13: 978-0471490661
• Product Dimensions: 9.3 x 6.5 x 1 inches
• Shipping Weight: 1.4 pounds (View shipping rates and policies)
• Average Customer Review: 4.0 out of 5 stars See all reviews (2 customer reviews)
• Amazon.com Sales Rank: #647,152 in Books (See Bestsellers in Books)

Customer Reviews

Most Helpful Customer Reviews

1 of 1 people found the following review helpful:

4.0 out of 5 stars Recommended, with reservations, April 15, 2008

By	Steven Bagley (Los Angeles, CA) - See all my reviews (REAL NAME)

This book is a survey of meta-analysis as applied to medical research. It covers fixed and random effects models, heterogeneity, publication bias, study quality and sensitivity analysis, and a number of more advanced topics, including Bayesian methods, problems with missing data, meta-analysis of other kinds of data, such as survival or observational data, and cumulative meta-analysis. The focus is on the statistical aspects of meta-analysis, not on how to conduct a literature search or code the sources, which are well documented elsewhere. The early part of the book is tutorial, and provides formulas for computing pooled effect sizes, and displays sample data sets in tables, along with corresponding graphical output. The latter part of the book discusses more advanced topics, but because of their inherent complexity, does not give complete details to allow reproducing the results. The mathematics is of moderate complexity. If you don't know about odds ratios, multivariate regression, and if notation such as y ~ N(0,1) leaves you puzzled, then this book is probably not for you. It makes only extremely brief use of linear algebra. It would be appropriate for quantitatively-inclined clinicians, or those learning about biostatistics and health services research. Although multi-authored, it has been edited for uniform style. It is quite readable, although there are a few annoying typos.

Negatives: the book was published in 2000, so it is not up-to-date, especially with respect to the capabilities of currently available software packages. The book's website no longer exists, so the claim that software code used in the examples is available to readers is a false one. This is a significant problem if you want to reproduce some of the Bayesian calculations, for example. Given these limitations, I feel it's not worth the $100+ price. A good book, but borrow it from the library.

1 of 1 people found the following review helpful:

4.0 out of 5 stars A personal review, May 12, 2007

By	Kurt Neumann (Vienna, Austria, Europe) - See all my reviews (REAL NAME)

This book has two big advantages: In my personal view it is written well for someone who has at least some basic statistical understanding and for me there are quite enough practical examples and illustrations of the chosen methodology. The second advantage in my opinion is its wealth of references at the end of every chapter.

Overall it covers almost all of the relevant methods and thus can be considered as a reference for the experienced statistician and as an easily comprehensible introduction to the beginner.

I think to recommend this book warmly to any reader who does not need the theoretical foundations of probability in meta-analysis.