Common Mistakes in Meta-Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Common Mistakes in Meta-Analysis write by Michael Borenstein. This book was released on 2019-08-14. Common Mistakes in Meta-Analysis available in PDF, EPUB and Kindle. Among the thousands of meta-analyses that have been published over the past several decades, there are a number of mistakes that appear on a fairly regular basis. This book outlines the most common mistakes, using examples in medicine, epidemiology, education, psychology, criminal justice, and other fields. For each, it explains why it is a mistake, the implications of the mistake, and how to correct the mistake. The book is intended primarily for researchers, and so the discussion is conceptual rather than statistical. The examples show the real-world consequences of the mistakes, explaining (for example) how the mistakes can lead to the adoption of interventions that may actually be harmful in some populations. The book includes a section with examples that show how to report the results of an analysis correctly. These examples can serve as templates for reporting an analysis, while avoiding the mistakes discussed in earlier chapters. The book's author is the co-author of the text Introduction to Meta-Analysis, the best-selling text in this field. In the current volume he draws on his experience teaching meta-analysis to thousands of researchers as well as his experience as a reviewer of meta-analyses for numerous journals.
Common Mistakes in Meta-Analysis
Common Mistakes in Meta-Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Common Mistakes in Meta-Analysis write by Michael Borenstein. This book was released on 2019-08-14. Common Mistakes in Meta-Analysis available in PDF, EPUB and Kindle.
Introduction to Meta-Analysis
Introduction to Meta-Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Introduction to Meta-Analysis write by Michael Borenstein. This book was released on 2021-04-06. Introduction to Meta-Analysis available in PDF, EPUB and Kindle. This 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. Written by four of the world’s foremost authorities on all aspects of meta-analysis, the new edition: Outlines the role of meta-analysis in the research process Shows how to compute effects sizes and treatment effects Explains the fixed-effect and random-effects models for synthesizing data Demonstrates how to assess and interpret variation in effect size across studies Explains how to avoid common mistakes in meta-analysis Discusses controversies in meta-analysis Includes 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)TM Download videos, class materials, and worked examples at www.Introduction-to-Meta-Analysis.com
Introduction to Meta-Analysis
Introduction to Meta-Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Introduction to Meta-Analysis write by Michael Borenstein. This book was released on 2011-08-24. Introduction to Meta-Analysis available in PDF, EPUB and Kindle. This book provides a clear and thorough introduction to meta-analysis, the process of synthesizing data from a series of separate studies. Meta-analysis has become a critically important tool in fields as diverse as medicine, pharmacology, epidemiology, education, psychology, business, and ecology. Introduction to Meta-Analysis: Outlines the role of meta-analysis in the research process Shows how to compute effects sizes and treatment effects Explains the fixed-effect and random-effects models for synthesizing data Demonstrates how to assess and interpret variation in effect size across studies Clarifies concepts using text and figures, followed by formulas and examples Explains how to avoid common mistakes in meta-analysis Discusses controversies in meta-analysis Features a web site with additional material and exercises A superb combination of lucid prose and informative graphics, written by four of the world’s leading experts on all aspects of meta-analysis. Borenstein, Hedges, Higgins, and Rothstein 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, who used pre-publication versions of some of the chapters, raved about the clarity of the explanations and examples. David Rindskopf, Distinguished Professor of Educational Psychology, City University of New York, Graduate School and University Center, & Editor of the Journal of Educational and Behavioral Statistics. 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. Jesse A. Berlin, ScD Introduction to Meta-Analysis is an excellent resource for novices and experts alike. The book provides a clear and comprehensive presentation of all basic and most advanced approaches to meta-analysis. This book will be referenced for decades. Michael A. McDaniel, Professor of Human Resources and Organizational Behavior, Virginia Commonwealth University
Doing Meta-Analysis with R
Doing Meta-Analysis with R - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Doing Meta-Analysis with R write by Mathias Harrer. This book was released on 2021-09-15. Doing Meta-Analysis with R available in PDF, EPUB and Kindle. Doing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including calculation and pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for publication bias, risk of bias assessments and plotting tools. Advanced but highly relevant topics such as network meta-analysis, multi-three-level meta-analyses, Bayesian meta-analysis approaches and SEM meta-analysis are also covered. A companion R package, dmetar, is introduced at the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide. The programming and statistical background covered in the book are kept at a non-expert level, making the book widely accessible. Features • Contains two introductory chapters on how to set up an R environment and do basic imports/manipulations of meta-analysis data, including exercises • Describes statistical concepts clearly and concisely before applying them in R • Includes step-by-step guidance through the coding required to perform meta-analyses, and a companion R package for the book
