{"product_id":"introduction-to-meta-analysis-isbn-9781119558354","title":"Introduction to Meta-Analysis","description":"\u003cp\u003e\u003cb\u003eA clear and thorough introduction to meta-analysis, the process of synthesizing data from a series of separate studies\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe first edition of this text was widely acclaimed for the clarity of the presentation, and quickly established itself as the definitive text in this field. The fully updated second edition includes new and expanded content on avoiding common mistakes in meta-analysis, understanding heterogeneity in effects, publication bias, and more. Several brand-new chapters provide a systematic \"how to\" approach to performing and reporting a meta-analysis from start to finish.\u003c\/p\u003e \u003cp\u003eWritten by four of the world's foremost authorities on all aspects of meta-analysis, the new edition:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eOutlines the role of meta-analysis in the research process\u003c\/li\u003e \u003cli\u003eShows how to compute effects sizes and treatment effects\u003c\/li\u003e \u003cli\u003eExplains the fixed-effect and random-effects models for synthesizing data\u003c\/li\u003e \u003cli\u003eDemonstrates how to assess and interpret variation in effect size across studies\u003c\/li\u003e \u003cli\u003eExplains how to avoid common mistakes in meta-analysis\u003c\/li\u003e \u003cli\u003eDiscusses controversies in meta-analysis\u003c\/li\u003e \u003cli\u003eIncludes access to a companion website containing videos, spreadsheets, data files, free software for prediction intervals, and step-by-step instructions for performing analyses using Comprehensive Meta-Analysis (CMA)\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eDownload videos, class materials, and worked examples at \u003cb\u003ewww.Introduction-to-Meta-Analysis.com\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\"This book offers the reader a unified framework for thinking about meta-analysis, and then discusses all elements of the analysis within that framework. The authors address a series of common mistakes and explain how to avoid them. As the editor-in-chief of the American Psychologist and former editor of Psychological Bulletin, I can say without hesitation that the quality of manuscript submissions reporting meta-analyses would be vastly better if researchers read this book.\"\u003cbr\u003e—\u003cb\u003eHarris Cooper\u003c\/b\u003e, Hugo L. Blomquist Distinguished Professor Emeritus of Psychology and Neuroscience, Editor-in-chief of the \u003ci\u003eAmerican Psychologist\u003c\/i\u003e, former editor of \u003ci\u003ePsychological Bulletin\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\"A superb combination of lucid prose and informative graphics, the authors provide a refreshing departure from cookbook approaches with their clear explanations of the what and why of meta-analysis. The book is ideal as a course textbook or for self-study. My students raved about the clarity of the explanations and examples.\" \u003cbr\u003e—\u003cb\u003eDavid Rindskopf\u003c\/b\u003e, Distinguished Professor of Educational Psychology, City University of New York, Graduate School and University Center, \u0026amp; Editor of the \u003ci\u003eJournal of Educational and Behavioral Statistics\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\"The approach taken by Introduction to Meta-analysis is intended to be primarily conceptual, and it is amazingly successful at achieving that goal. The reader can comfortably skip the formulas and still understand their application and underlying motivation. For the more statistically sophisticated reader, the relevant formulas and worked examples provide a superb practical guide to performing a meta-analysis. The book provides an eclectic mix of examples from education, social science, biomedical studies, and even ecology. For anyone considering leading a course in meta-analysis, or pursuing self-directed study, Introduction to Meta-analysis would be a clear first choice.\" \u003cbr\u003e—\u003cb\u003eJesse A. Berlin\u003c\/b\u003e, SCD\u003c\/p\u003e \u003cp\u003eList of Tables xv\u003c\/p\u003e \u003cp\u003eList of Figures xix\u003c\/p\u003e \u003cp\u003eAcknowledgements xxv\u003c\/p\u003e \u003cp\u003ePreface xxvii\u003c\/p\u003e \u003cp\u003ePreface to the Second Edition xxxv\u003c\/p\u003e \u003cp\u003eWebsite xxxvii\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 1: Introduction\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1 How a Meta-Analysis Works 3\u003c\/p\u003e \u003cp\u003e2 Why Perform a Meta-Analysis 9\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 2: Effect Size and Precision\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3 Overview 17\u003c\/p\u003e \u003cp\u003e4 Effect Sizes Based On Means 21\u003c\/p\u003e \u003cp\u003e5 Effect Sizes Based On Binary Data (2 × 2 Tables) 33\u003c\/p\u003e \u003cp\u003e6 Effect Sizes Based On Correlations 39\u003c\/p\u003e \u003cp\u003e7 Converting Among Effect Sizes 43\u003c\/p\u003e \u003cp\u003e8 Factors That Affect Precision 49\u003c\/p\u003e \u003cp\u003e9 Concluding Remarks 55\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 3: Fixed-Effect Versus Random-Effects Models\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10 Overview 59\u003c\/p\u003e \u003cp\u003e11 Fixed-Effect Model 61\u003c\/p\u003e \u003cp\u003e12 Random-Effects Model 65\u003c\/p\u003e \u003cp\u003e13 Fixed-Effect Versus Random-Effects Models 71\u003c\/p\u003e \u003cp\u003e14 Worked Examples (Part 1) 81\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 4: Heterogeneity\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e15 Overview 97\u003c\/p\u003e \u003cp\u003e16 Identifying and Quantifying Heterogeneity 99\u003c\/p\u003e \u003cp\u003e17 Prediction Intervals 119\u003c\/p\u003e \u003cp\u003e18 Worked Examples (Part 2) 127\u003c\/p\u003e \u003cp\u003e19 An Intuitive Look At Heterogeneity 139\u003c\/p\u003e \u003cp\u003e20 Classifying Heterogeneity As Low, Moderate, Or High 155\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 5: Explaining Heterogeneity\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e21 Subgroup Analyses 161\u003c\/p\u003e \u003cp\u003e22 Meta-Regression 197\u003c\/p\u003e \u003cp\u003e23 Notes On Subgroup Analyses and Meta-Regression 213\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 6: Putting It All In Context\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e24 Looking At the Whole Picture 223\u003c\/p\u003e \u003cp\u003e25 Limitations of the Random-Effects Model 233\u003c\/p\u003e \u003cp\u003e26 Knapp–Hartung Adjustment 243\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 7: Complex Data Structures\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e27 Overview 253\u003c\/p\u003e \u003cp\u003e28 Independent Subgroups Within a Study 255\u003c\/p\u003e \u003cp\u003e29 Multiple Outcomes or Time-Points Within A Study 263\u003c\/p\u003e \u003cp\u003e30 Multiple Comparisons Within a Study 277\u003c\/p\u003e \u003cp\u003e31 Notes On Complex Data Structures 281\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 8: Other Issues\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e32 Overview 287\u003c\/p\u003e \u003cp\u003e33 Vote Counting – A New Name For An Old Problem 289\u003c\/p\u003e \u003cp\u003e34 Power Analysis For Meta-Analysis 295\u003c\/p\u003e \u003cp\u003e35 Publication Bias 313\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 9: Issues Related To Effect Size\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e36 Overview 335\u003c\/p\u003e \u003cp\u003e37 Effect Sizes Rather Than P-Values 337\u003c\/p\u003e \u003cp\u003e38 Simpson’s Paradox 343\u003c\/p\u003e \u003cp\u003e39 Generality of the Basic Inverse-Variance Method 349\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 10: Further Methods\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e40 Overview 361\u003c\/p\u003e \u003cp\u003e41 Meta-Analysis Methods Based On Direction and P-Values 363\u003c\/p\u003e \u003cp\u003e42 Further Methods For Dichotomous Data 369\u003c\/p\u003e \u003cp\u003e43 Psychometric Meta-Analysis 377\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 11: Meta-Analysis In Context\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e44 Overview 391\u003c\/p\u003e \u003cp\u003e45 When Does It Make Sense To Perform a Meta-Analysis? 393\u003c\/p\u003e \u003cp\u003e46 Reporting The Results of a Meta-Analysis 401\u003c\/p\u003e \u003cp\u003e47 Cumulative Meta-Analysis 407\u003c\/p\u003e \u003cp\u003e48 Criticisms of Meta-Analysis 413\u003c\/p\u003e \u003cp\u003e49 Comprehensive Meta-Analysis Software 425\u003c\/p\u003e \u003cp\u003e50 How To Explain the Results of An Analysis 443\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 12: Resources\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e51 Software For Meta-Analysis 471\u003c\/p\u003e \u003cp\u003e52 Web Sites, Societies, Journals, and Books 473\u003c\/p\u003e \u003cp\u003eWeb sites 473\u003c\/p\u003e \u003cp\u003eProfessional societies 476\u003c\/p\u003e \u003cp\u003eJournals 476\u003c\/p\u003e \u003cp\u003eSpecial issues dedicated to meta-analysis 477\u003c\/p\u003e \u003cp\u003eBooks on systematic review methods and meta-analysis 477\u003c\/p\u003e \u003cp\u003eReferences 479\u003c\/p\u003e \u003cp\u003eIndex 491\u003c\/p\u003e \u003cp\u003e\u003cb\u003eIntroduction to Meta-Analysis, Second Edition\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThis book provides a clear and thorough introduction to meta-analysis, the process of synthesizing data from a series of separate studies. The first edition of this text was widely acclaimed for the clarity of the presentation, and quickly established itself as the definitive text in this field. The fully updated second edition includes new and expanded content on avoiding common mistakes in meta-analysis, understanding heterogeneity in effects, publication bias, and more. Several brand-new chapters provide a systematic “how to” approach to performing and reporting a meta-analysis from start to finish.\u003cbr\u003e\u003cbr\u003eWritten by four of the world’s foremost authorities on all aspects of meta-analysis, the new edition:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eOutlines the role of meta-analysis in the research process\u003c\/li\u003e \u003cli\u003eShows how to compute effects sizes and treatment effects\u003c\/li\u003e \u003cli\u003eExplains the fixed-effect and random-effects models for synthesizing data\u003c\/li\u003e \u003cli\u003eDemonstrates how to assess and interpret variation in effect size across studies\u003c\/li\u003e \u003cli\u003eExplains how to avoid common mistakes in meta-analysis\u003c\/li\u003e \u003cli\u003eDiscusses controversies in meta-analysis\u003c\/li\u003e \u003cli\u003eIncludes access to a companion website containing videos, spreadsheets, data files, free software for prediction intervals, and step-by-step instructions for performing analyses using Comprehensive Meta-Analysis (CMA) ™\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eDownload videos, class materials, and worked examples at \u003cb\u003ewww.Introduction-to-Meta-Analysis.com\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eThis book offers the reader a unified framework for thinking about meta-analysis, and then discusses all elements of the analysis within that framework. The authors address a series of common mistakes and explain how to avoid them. As the editor-in-chief of the American Psychologist and former editor of Psychological Bulletin, I can say without hesitation that the quality of manuscript submissions reporting meta-analyses would be vastly better if researchers read this book.\u003cbr\u003e\u003c\/i\u003eHarris Cooper, Hugo L. Blomquist Distinguished Professor Emeritus of Psychology and Neuroscience, Editor-in-chief of the American Psychologist, former editor of Psychological Bulletin\u003c\/p\u003e \u003cp\u003e\u003ci\u003eA superb combination of lucid prose and informative graphics, the authors provide a refreshing departure from cookbook approaches with their clear explanations of the what and why of meta-analysis. The book is ideal as a course textbook or for self-study. My students raved about the clarity of the explanations and examples.\u003cbr\u003e\u003c\/i\u003eDavid Rindskopf, Distinguished Professor of Educational Psychology, City University of New York, Graduate School and University Center, \u0026amp; Editor of the Journal of Educational and Behavioral Statistics.\u003c\/p\u003e \u003cp\u003e\u003ci\u003eThe approach taken by Introduction to Meta-analysis is intended to be primarily conceptual, and it is amazingly successful at achieving that goal. The reader can comfortably skip the formulas and still understand their application and underlying motivation. For the more statistically sophisticated reader, the relevant formulas and worked examples provide a superb practical guide to performing a meta-analysis. The book provides an eclectic mix of examples from education, social science, biomedical studies, and even ecology. For anyone considering leading a course in meta-analysis, or pursuing self-directed study, Introduction to Meta-analysis would be a clear first choice.\u003c\/i\u003e\u003cbr\u003eJesse A. Berlin, SCD\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989462565093,"sku":"NP9781119558354","price":65.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781119558354.jpg?v=1761784198","url":"https:\/\/k12savings.com\/products\/introduction-to-meta-analysis-isbn-9781119558354","provider":"K12savings","version":"1.0","type":"link"}