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Statistical MetaAnalysis with Applications,Used
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An accessible introduction to performing metaanalysis across various areas of researchThe practice of metaanalysis allows researchers to obtain findings from various studies and compile them to verify and form one overall conclusion. Statistical MetaAnalysis with Applications presents the necessary statistical methodologies that allow readers to tackle the four main stages of metaanalysis: problem formulation, data collection, data evaluation, and data analysis and interpretation. Combining the authors' expertise on the topic with a wealth of uptodate 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: Metaanalysis regression proceduresMultipleendpoint and multipletreatment studiesThe Bayesian approach to metaanalysisPublication biasVote counting proceduresMethods for combining individual tests and combining individual estimatesUsing metaanalysis to analyze binary and ordinal categorical dataNumerous workedout examples in each chapter provide the reader with a stepbystep understanding of the presented methods. All exercises can be computed using the R and SAS 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 MetaAnalysis with Applications is a valuable supplement for courses in biostatistics, business, public health, and social research at the upperundergraduate and graduate levels. It is also an excellent reference for applied statisticians working in industry, academia, and government.
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