MadMethods 1-3
MadMethods 1-3

Author: Paul D Ellis

Publisher:

Published: 2020-09

Total Pages: 266

ISBN-13: 9781927230626

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Three books in one! Get the entire MadMethods series in this special edition for one low price! 1. Effect Size Matters: Learn how to do research that matters and get results that make sense. This plain-English guide will show you how to the answer the dreaded "So what?" question. It will teach you how to interpret the substantive or practical significance of your results and convey them in ways that are meaningful to stakeholders. 2. Statistical Power Trip: Many studies lack the statistical power to find effects. This jargon-free guide will show you how to boost the power of underpowered research and design studies that succeed. Learn how to calculate sample sizes and boost your funding prospects with power analyses that dazzle. 3. Meta-Analysis Made Easy: Will your research make a unique contribution? Or are you reinventing the wheel? Using examples proven in the field and tested in the classroom, this quick guide to meta-analysis will show you how to draw conclusions even from inconclusive studies. It will help you discover patterns of meaning in disparate research and uncover gold mines for further research. What readers are saying: ★★★★★ "Who knew statistics was this interesting? I learned a lot!" ★★★★★ "I was impressed by the clarity (and very amusing examples) in this text." ★★★★★ "Some people write to impress and others to instruct. This book is for instruction." ★★★★★ "Exceptionally lucid overview of power analysis, effect sizes, and sample size calculations." ★★★★★ "The clearest presentation of three complex and important subjects." ★★★★★ "An easy read on a complex topic. Great resource!" ★★★★★ "Clearly explains the concepts behind statistical mechanics." ★★★★★ "Easy to read, understand, and follow." Get your copy now.

A Practical Guide to Modern Methods of Meta-analysis
A Practical Guide to Modern Methods of Meta-analysis

Author: Larry V. Hedges

Publisher:

Published: 1989

Total Pages: 92

ISBN-13:

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Methods for meta-analysis have evolved dramatically since Gene Glass first proposed the term in 1976. Since that time statistical and nonstatistical aspects of methodology for meta-analysis have been developing at a steady pace. This guide is an attempt to provide a practical introduction to rigorous procedures in the meta-analysis of social science research. It approaches the use of modern statistical methods in meta-analysis from the perspective of a potential user. The treatment is limited to meta-analysis of studies of between-group comparisons using the standardized mean difference as an index of effect magnitude. This guide is organized according to a variant of Cooper's stages of the research review process: (1) problem formulation; (2) data collection and data evaluation, data analysis and interpretation; and (3) presentation of results. Although each stage is discussed, the greatest emphasis is placed on the stage of data analysis and interpretation. Examples from a synthesis of research on the effects of science curricula are used throughout for illustration. Because this book is intended to be a practical guide, the references are provided primarily to exemplify issues or techniques rather than to provide theoretical discussions or derivations. (CW)

Meta Analysis
Meta Analysis

Author: Elena Kulinskaya

Publisher: John Wiley & Sons

Published: 2008-04-14

Total Pages: 293

ISBN-13: 0470028645

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Meta Analysis: A Guide to Calibrating and Combining Statistical Evidence acts as a source of basic methods for scientists wanting to combine evidence from different experiments. The authors aim to promote a deeper understanding of the notion of statistical evidence. The book is comprised of two parts – The Handbook, and The Theory. The Handbook is a guide for combining and interpreting experimental evidence to solve standard statistical problems. This section allows someone with a rudimentary knowledge in general statistics to apply the methods. The Theory provides the motivation, theory and results of simulation experiments to justify the methodology. This is a coherent introduction to the statistical concepts required to understand the authors’ thesis that evidence in a test statistic can often be calibrated when transformed to the right scale.

Statistical Methods for Meta-Analysis
Statistical Methods for Meta-Analysis

Author: Larry V. Hedges

Publisher: Academic Press

Published: 2014-06-28

Total Pages: 392

ISBN-13: 0080570658

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The main purpose of this book is to address the statistical issues for integrating independent studies. There exist a number of papers and books that discuss the mechanics of collecting, coding, and preparing data for a meta-analysis , and we do not deal with these. Because this book concerns methodology, the content necessarily is statistical, and at times mathematical. In order to make the material accessible to a wider audience, we have not provided proofs in the text. Where proofs are given, they are placed as commentary at the end of a chapter. These can be omitted at the discretion of the reader.Throughout the book we describe computational procedures whenever required. Many computations can be completed on a hand calculator, whereas some require the use of a standard statistical package such as SAS, SPSS, or BMD. Readers with experience using a statistical package or who conduct analyses such as multiple regression or analysis of variance should be able to carry out the analyses described with the aid of a statistical package.

Introduction to Meta-Analysis
Introduction to Meta-Analysis

Author: Michael Borenstein

Publisher: John Wiley & Sons

Published: 2011-08-24

Total Pages: 350

ISBN-13: 1119964377

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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

Author: Mathias Harrer

Publisher: CRC Press

Published: 2021-09-15

Total Pages: 500

ISBN-13: 1000435636

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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

Systematic Reviews and Meta-Analysis
Systematic Reviews and Meta-Analysis

Author: Jacqueline Corcoran

Publisher: Oxford University Press

Published: 2008-02-13

Total Pages: 211

ISBN-13: 0190296119

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When used in tandem, systematic reviews and meta-analysis-- two distinct but highly compatible approaches to research synthesis-- form a powerful, scientific approach to analyzing previous studies. But to see their full potential, a social work researcher must be versed in the foundational processes underlying them. This pocket guide to Systematic Reviews and Meta-Analysis illuminates precisely that practical groundwork. In clear, step-by-step terms, the authors explain how to format topics, locate and screen studies, extract and assess data, pool effect sizes, determine bias, and interpret the results, showing readers how to combine reviewing and meta-analysis correctly and effectively. Each chapter contains vivid social work examples and concludes with a concise summary and notes on further reading, while the books glossary and handy checklists and sample search and data extraction forms maximize the books usefulness. Highlighting the concepts necessary to understand, critique, and conduct research synthesis, this brief and highly readable introduction is a terrific resource for students and researchers alike.

Handbook of Meta-analysis in Ecology and Evolution
Handbook of Meta-analysis in Ecology and Evolution

Author: Julia Koricheva

Publisher: Princeton University Press

Published: 2013-04-21

Total Pages: 514

ISBN-13: 0691137293

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Meta-analysis is a powerful statistical methodology for synthesizing research evidence across independent studies. This is the first comprehensive handbook of meta-analysis written specifically for ecologists and evolutionary biologists, and it provides an invaluable introduction for beginners as well as an up-to-date guide for experienced meta-analysts. The chapters, written by renowned experts, walk readers through every step of meta-analysis, from problem formulation to the presentation of the results. The handbook identifies both the advantages of using meta-analysis for research synthesis and the potential pitfalls and limitations of meta-analysis (including when it should not be used). Different approaches to carrying out a meta-analysis are described, and include moment and least-square, maximum likelihood, and Bayesian approaches, all illustrated using worked examples based on real biological datasets. This one-of-a-kind resource is uniquely tailored to the biological sciences, and will provide an invaluable text for practitioners from graduate students and senior scientists to policymakers in conservation and environmental management. Walks you through every step of carrying out a meta-analysis in ecology and evolutionary biology, from problem formulation to result presentation Brings together experts from a broad range of fields Shows how to avoid, minimize, or resolve pitfalls such as missing data, publication bias, varying data quality, nonindependence of observations, and phylogenetic dependencies among species Helps you choose the right software Draws on numerous examples based on real biological datasets

Meta-Analysis for Explanation
Meta-Analysis for Explanation

Author: Thomas D. Cook

Publisher: Russell Sage Foundation

Published: 1992-04-27

Total Pages: 393

ISBN-13: 1610441338

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Social science research often yields conflicting results: Does juvenile delinquent rehabilitation work? Is teenage pregnancy prevention effective? In an effort to improve the value of research for shaping social policy, social scientists are increasingly employing a powerful technique called meta-analysis. By systematically pulling together findings of a particular research problem, meta-analysis allows researchers to synthesize the results of multiple studies and detect statistically significant patterns among them. Meta-Analysis for Explanation brings exemplary illustrations of research synthesis together with expert discussion of the use of meta-analytic techniques. The emphasis throughout is on the explanatory applications of meta-analysis, a quality that makes this casebook distinct from other treatments of this methodology. The book features four detailed case studies by Betsy Jane Becker, Elizabeth C. Devine, Mark W. Lipsey, and William R. Shadish, Jr. These are offered as meta-analyses that seek both to answer the descriptive questions to which research synthesis is traditionally directed in the health and social sciences, and also to explore how a more systematic method of explanation might enhance the policy yield of research reviews. To accompany these cases, a group of the field's leading scholars has written several more general chapters that discuss the history of research synthesis, the use of meta-analysis and its value for scientific explanation, and the practical issues and challenges facing researchers who want to try this new technique. As a practical resource, Meta-Analysis for Explanation guides social scientists to greater levels of sophistication in their efforts to synthesize the results of social research. "This is an important book...[it is] another step in the continuing exploration of the wider implications and powers of meta-analytic methods." —Contemporary Psychology

Statistical Meta-Analysis with Applications
Statistical Meta-Analysis with Applications

Author: Joachim Hartung

Publisher: John Wiley & Sons

Published: 2011-09-20

Total Pages: 215

ISBN-13: 1118210964

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An accessible introduction to performing meta-analysis across various areas of research The 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 procedures Multiple-endpoint and multiple-treatment studies The Bayesian approach to meta-analysis Publication bias Vote counting procedures Methods for combining individual tests and combining individual estimates Using meta-analysis to analyze binary and ordinal categorical data Numerous 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.