Statistical Meta-Analysis with Applications / Edition 1

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Overview

An accessible introduction to performing meta-analysis across various areas of research

The practice of meta-analysis allows researchers to obtain findings from various studies and compile them to verify and form one overall conclusion. Statistical Meta-Analysis with Applications presents the necessary statistical methodologies that allow readers to tackle the four main stages of meta-analysis: problem formulation, data collection, data evaluation, and data analysis and interpretation. Combining the authors' expertise on the topic with a wealth of up-to-date information, this book successfully introduces the essential statistical practices for making thorough and accurate discoveries across a wide array of diverse fields, such as business, public health, biostatistics, and environmental studies.

Two main types of statistical analysis serve as the foundation of the methods and techniques: combining tests of effect size and combining estimates of effect size. Additional topics covered include:

  • Meta-analysis regression procedures
  • Multiple-endpoint and multiple-treatment studies
  • The Bayesian approach to meta-analysis
  • Publication bias
  • Vote counting procedures
  • Methods for combining individual tests and combining individual estimates
  • Using meta-analysis to analyze binary and ordinal categorical data

Numerous worked-out examples in each chapter provide the reader with a step-by-step understanding of the presented methods. All exercises can be computed using the R and SASĀ® software packages, which are both available via the book's related Web site. Extensive references are also included, outlining additional sources for further study.

Requiring only a working knowledge of statistics, Statistical Meta-Analysis with Applications is a valuable supplement for courses in biostatistics, business, public health, and social research at the upper-undergraduate and graduate levels. It is also an excellent reference for applied statisticians working in industry, academia, and government.

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Editorial Reviews

From the Publisher
"The strength of this book is certainly the detailed development and presentation of inference for normal fixed and random effects models as applied in meta-analysis and similar studies, such as inter-laboratory studies. A particularly well done part of the book centers on homogeneity testing and on confidence interval estimation of the so-called heterogeneity parameter in the standard random effects model." (Journal of Biopharmaceutical Statistics, January 2010)

"The authors have written a good guide to a broad section of the methods available for statistical meta-analysis." (Mathematical Reviews, 2009)

"[The authors], active researchers themselves, have done a commendable job in writing this introductory book noted for its clarity and style of presentation and coverage of some totally new topics." (Choice, April 2009)

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