دانلود کتاب Statistical Meta-Analysis with Applications (Wiley Series in Probability and Statistics)

An accessible introduction to performing meta-analysis across various areas of researchThe 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 proceduresMultiple-endpoint and multiple-treatment studiesThe Bayesian approach to meta-analysisPublication biasVote counting proceduresMethods for combining individual tests and combining individual estimatesUsing meta-analysis to analyze binary and ordinal categorical dataNumerous 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 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 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.