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Methods for Meta-Analysis in Medical Research


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Authors:
Alex J. Sutton, Keith R. Abrams, David R. Jones, Trevor A. Sheldon, and Fujian Song
Publisher: Wiley
Copyright: 2000
ISBN-13: 978-0-471-49066-1
Pages: 317; hardcover
Authors:
Alex J. Sutton, Keith R. Abrams, David R. Jones, Trevor A. Sheldon, and Fujian Song
Publisher: Wiley
Copyright: 2000
ISBN-13:
Pages: 317; eBook
Price: $0.00
Authors:
Alex J. Sutton, Keith R. Abrams, David R. Jones, Trevor A. Sheldon, and Fujian Song
Publisher: Wiley
Copyright: 2000
ISBN-13:
Pages: 317; Kindle
Price: $

Comment from the Stata technical group

Meta-analysis as a statistical and scientific tool has grown immensely in popularity over the last decade as a way to systematically present new research results in the proper context, given all previous related work. This text covers much of the statistical methodology used by meta-analysts, from the most basic to the advanced, and is ideal for self-study as it requires little background knowledge of statistics. The authors do a good job of presenting their concepts free of mathematical theory, which is of little use to the practicing researcher.

The book begins in part A with some basic meta-analysis terminology and biostatistical terms, such as odds, odds ratios, and relative risks. Part A then continuous with a discussion of heterogeneity, the application of fixed-effects and random-effects methods for combining study estimates, publication bias, sensitivity analysis, and graphical techniques. Part B covers Bayesian methods (which fit naturally with the concept of meta-analysis), the meta-analysis of individual patient data, missing data, the meta-analysis of nonstandard data types, multiple and correlated outcome measures, observational studies, survival data, and miscellaneous topics.

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