Description: FREE SHIPPING UK WIDE Applied Meta-Analysis with R and Stata by Karl E. Peace, Ding-Geng Chen In biostatistical research and courses, practitioners and students often lack a thorough understanding of how to apply statistical methods to synthesize biomedical and clinical trial data. Filling this knowledge gap, this book shows how to implement statistical meta-analysis methods to real data using R and Stata. FORMAT Paperback CONDITION Brand New Publisher Description Review of the First Edition:The authors strive to reduce theory to a minimum, which makes it a self-learning text that is comprehensible for biologists, physicians, etc. who lack an advanced mathematics background. Unlike in many other textbooks, R is not introduced with meaningless toy examples; instead the reader is taken by the hand and shown around some analyses, graphics, and simulations directly relating to meta-analysis… A useful hands-on guide for practitioners who want to familiarize themselves with the fundamentals of meta-analysis and get started without having to plough through theorems and proofs.—Journal of Applied StatisticsStatistical Meta-Analysis with R and Stata, Second Edition provides a thorough presentation of statistical meta-analyses (MA) with step-by-step implementations using R/Stata. The authors develop analysis step by step using appropriate R/Stata functions, which enables readers to gain an understanding of meta-analysis methods and R/Stata implementation so that they can use these two popular software packages to analyze their own meta-data. Each chapter gives examples of real studies compiled from the literature. After presenting the data and necessary background for understanding the applications, various methods for analyzing meta-data are introduced. The authors then develop analysis code using the appropriate R/Stata packages and functions.Whats New in the Second Edition: Adds Stata programs along with the R programs for meta-analysis Updates all the statistical meta-analyses with R/Stata programs Covers fixed-effects and random-effects MA, meta-regression, MA with rare-event, and MA-IPD vs MA-SS Adds five new chapters on multivariate MA, publication bias, missing data in MA, MA in evaluating diagnostic accuracy, and network MASuitable as a graduate-level text for a meta-data analysis course, the book is also a valuable reference for practitioners and biostatisticians (even those with little or no experience in using R or Stata) in public health, medical research, governmental agencies, and the pharmaceutical industry. Author Biography Ding-Geng (Din) Chen is a fellow of American Statistical Association and currently the Wallace H. Kuralt Distinguished Professor at the University of North Carolina-Chapel Hill, USA. Formerly, he was a Professor of Biostatistics at the University of Rochester, New York, USA, the Karl E. Peace Endowed Eminent Scholar Chair and professor in Biostatistics in the Jiann-Ping Hsu College of Public Health at Georgia Southern University, USA, and a professor of statistics at South Dakota Stata University, USA. Dr. Chens research interests include clinical trial biostatistical methodological development in Bayesian models, survival analysis, multi-level modelling and longitudinal data analysis, and statistical meta-analysis. He has published more than 200 refereed papers and co-authored/co-edited 30 book in statistics. Karl E. Peace is the Georgia Cancer Coalition Distinguished Cancer Scholar, Founding Director of the Center for Biostatistics, Professor of Biostatistics, and Senior Research Scientist in the Jiann-Ping Hsu College of Public Health at Georgia Southern University (GSU). Dr. Peace has made pivotal contributions in the development and approval of drugs to treat numerous diseases and disorders. A fellow of the ASA, he has been a recipient of many honors, including the Drug Information Association Outstanding Service Award, the American Public Health Association Statistics Section Award, The First recipient of the Presidents Medal for outstanding contributions to GSU, and recognition by the Georgia and US Houses of Representatives, and the Virginia House of Delegates. Table of Contents 1. Introduction to R and Stata for Meta-Analysis2. Research Protocol for Meta-Analyses3. Fixed-E ects and Random-E ects in Meta-Analysis4. Meta-Analysis with Binary Data5. Meta-Analysis for Continuous Data6. Heterogeneity in Meta-Analysis7. Meta-Regression8. Multivariate Meta-Analysis9. Publication Bias in Meta-Analysis10. Strategies to Handle Missing Data in Meta-Analysis11. Meta-Analysis for Evaluating Diagnostic Accuracy12. Network Meta-Analysis13. Meta-Analysis for Rare Events14. Meta-Analyses with Individual Patient-Level Data versus Summary Statistics15. Other R/Stata Packages for Meta-Analysis Review "The strengths of the second edition continue those of the first edition... A summary and discussion close the chapters, providing professionally generous recommendations for additional reading, software, and websites. Clearly, an applied hands-on approach intended to facilitate quickly moving readers to performing informed meta-data analyses."- Thomas E. Bradstreet, Journal of Biopharmaceutical Statistics, July 2022 Review Quote "The strengths of the second edition continue those of the first edition... A summary and discussion close the chapters, providing professionally generous recommendations for additional reading, software, and websites. Clearly, an applied hands-on approach intended to facilitate quickly moving readers to performing informed meta-data analyses." - Thomas E. Bradstreet, Journal of Biopharmaceutical Statistics, July 2022 Details ISBN0367709341 Author Ding-Geng Chen Pages 424 Publisher Taylor & Francis Ltd Year 2022 ISBN-10 0367709341 ISBN-13 9780367709341 Publication Date 2022-09-26 UK Release Date 2022-09-26 Edition 2nd Format Paperback Place of Publication London Country of Publication United Kingdom AU Release Date 2022-09-26 NZ Release Date 2022-09-26 Illustrations 23 Tables, black and white; 63 Illustrations, black and white Edition Description 2nd edition Series Chapman & Hall/CRC Biostatistics Series Alternative 9780367183837 DEWEY 610.727 Audience Tertiary & Higher Education Imprint Chapman & Hall/CRC We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! 30 DAY RETURN POLICY No questions asked, 30 day returns! FREE DELIVERY No matter where you are in the UK, delivery is free. 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