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„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)
An accessible introduction to performing meta-analysis acrossvarious areas of research
The practice of meta-analysis allows researchers to obtainfindings from various studies and compile them to verify and formone overall conclusion. Statistical Meta-Analysis with Applicationspresents the necessary statistical methodologies that allow readersto tackle the four main stages of meta-analysis: problemformulation, data collection, data evaluation, and data analysisand interpretation. Combining the authors' expertise on the topicwith a wealth of up-to-date information, this book successfullyintroduces the essential statistical practices for making thoroughand accurate discoveries across a wide array of diverse fields, such as business, public health, biostatistics, and environmentalstudies.
Two main types of statistical analysis serve as the foundationof the methods and techniques: combining tests of effect size andcombining estimates of effect size. Additional topics coveredinclude:
* 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 individualestimates
* Using meta-analysis to analyze binary and ordinal categoricaldata
Numerous worked-out examples in each chapter provide the readerwith a step-by-step understanding of the presented methods. Allexercises can be computed using the R and SAS software packages, which are both available via the book's related Web site. Extensivereferences are also included, outlining additional sources forfurther study.
Requiring only a working knowledge of statistics, StatisticalMeta-Analysis with Applications is a valuable supplement forcourses in biostatistics, business, public health, and socialresearch at the upper-undergraduate and graduate levels. It is alsoan excellent reference for applied statisticians working inindustry, academia, and government.
The practice of meta-analysis allows researchers to obtainfindings from various studies and compile them to verify and formone overall conclusion. Statistical Meta-Analysis with Applicationspresents the necessary statistical methodologies that allow readersto tackle the four main stages of meta-analysis: problemformulation, data collection, data evaluation, and data analysisand interpretation. Combining the authors' expertise on the topicwith a wealth of up-to-date information, this book successfullyintroduces the essential statistical practices for making thoroughand accurate discoveries across a wide array of diverse fields, such as business, public health, biostatistics, and environmentalstudies.
Two main types of statistical analysis serve as the foundationof the methods and techniques: combining tests of effect size andcombining estimates of effect size. Additional topics coveredinclude:
* 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 individualestimates
* Using meta-analysis to analyze binary and ordinal categoricaldata
Numerous worked-out examples in each chapter provide the readerwith a step-by-step understanding of the presented methods. Allexercises can be computed using the R and SAS software packages, which are both available via the book's related Web site. Extensivereferences are also included, outlining additional sources forfurther study.
Requiring only a working knowledge of statistics, StatisticalMeta-Analysis with Applications is a valuable supplement forcourses in biostatistics, business, public health, and socialresearch at the upper-undergraduate and graduate levels. It is alsoan excellent reference for applied statisticians working inindustry, academia, and government.
