Applied Meta-Analysis for Social Science Research

Applied Meta-Analysis for Social Science Research

Author: Noel A. Card

Publisher: Guilford Publications

Published: 2015-10-06

Total Pages: 401

ISBN-13: 1462525008

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Offering pragmatic guidance for planning and conducting a meta-analytic review, this book is written in an engaging, nontechnical style that makes it ideal for graduate course use or self-study. The author shows how to identify questions that can be answered using meta-analysis, retrieve both published and unpublished studies, create a coding manual, use traditional and unique effect size indices, and write a meta-analytic review. An ongoing example illustrates meta-analytic techniques. In addition to the fundamentals, the book discusses more advanced topics, such as artifact correction, random- and mixed-effects models, structural equation representations, and multivariate procedures. User-friendly features include annotated equations; discussions of alternative approaches; and "Practical Matters" sections that give advice on topics not often discussed in other books, such as linking meta-analytic results with theory and the utility of meta-analysis software programs. ÿ


Research Synthesis and Meta-Analysis

Research Synthesis and Meta-Analysis

Author: Harris Cooper

Publisher: SAGE Publications

Published: 2015-12-24

Total Pages: 189

ISBN-13: 1483347044

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The Fifth Edition of Harris Cooper′s bestselling text offers practical advice on how to conduct a synthesis of research in the social, behavioral, and health sciences. The book is written in plain language with four running examples drawn from psychology, education, and health science. With ample coverage of literature searching and the technical aspects of meta-analysis, this one-of-a-kind book applies the basic principles of sound data gathering to the task of producing a comprehensive assessment of existing research.


Research Synthesis and Meta-Analysis

Research Synthesis and Meta-Analysis

Author: Harris Cooper

Publisher: SAGE

Published: 2010

Total Pages: 281

ISBN-13: 1412937051

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Providing researchers with a practical and accessible advice, the Fourth Edition of the lauded Research Synthesis and Meta-Analysis offers thoroughly updated information. Author Harris M. Cooper draws on more than 30 years of experience to show readers how to conduct a comprehensive synthesis of past research.


Meta-Analytic Procedures for Social Research

Meta-Analytic Procedures for Social Research

Author: Robert Rosenthal

Publisher: SAGE

Published: 1991-05

Total Pages: 172

ISBN-13: 9780803942462

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Considers meta-analytic procedures (the quantitative summary of a research domain) in sufficient detail for readers either to carry them out for themselves, or evaluate the procedures when used by others and offers advice about the applicability of these techniques to specific research questions.


Methods of Meta-Analysis

Methods of Meta-Analysis

Author: John E Hunter

Publisher: SAGE

Published: 2004-04-07

Total Pages: 620

ISBN-13: 9781412904797

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Covering the most important developments in meta-analysis from 1990 to 2004, this text presents new patterns in research findings as well as updated information on existing topics.


Applied Meta-Analysis with R

Applied Meta-Analysis with R

Author: Ding-Geng (Din) Chen

Publisher: CRC Press

Published: 2013-05-03

Total Pages: 338

ISBN-13: 1466505990

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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, Applied Meta-Analysis with R shows how to implement statistical meta-analysis methods to real data using R. Drawing on their extensive research and teaching experiences, the authors provide detailed, step-by-step explanations of the implementation of meta-analysis methods using R. 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 packages and functions. This systematic approach helps readers thoroughly understand the analysis methods and R implementation, enabling them to use R and the methods to analyze their own meta-data. Suitable 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) in public health, medical research, governmental agencies, and the pharmaceutical industry.


Meta-Study of Qualitative Health Research

Meta-Study of Qualitative Health Research

Author: Barbara L. Paterson

Publisher: SAGE

Published: 2001-06

Total Pages: 180

ISBN-13: 9780761924159

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This title provides step-by-step directions for how to conduct a meta-study, as well as recommendations for tools and standards for the application of this approach.


Social Science Research

Social Science Research

Author: Anol Bhattacherjee

Publisher: CreateSpace

Published: 2012-04-01

Total Pages: 156

ISBN-13: 9781475146127

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This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages.


Applied Meta-Analysis with R and Stata

Applied Meta-Analysis with R and Stata

Author: Ding-Geng (Din) Chen

Publisher: CRC Press

Published: 2021-03-31

Total Pages: 423

ISBN-13: 0429590237

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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 Statistics Statistical 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. What’s 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 MA Suitable 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.


Best Practices in Quantitative Methods

Best Practices in Quantitative Methods

Author: Jason W. Osborne

Publisher: SAGE

Published: 2008

Total Pages: 609

ISBN-13: 1412940656

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The contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences. The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better. Key Features: Describes important implicit knowledge to readers: The chapters in this volume explain the important details of seemingly mundane aspects of quantitative research, making them accessible to readers and demonstrating why it is important to pay attention to these details. Compares and contrasts analytic techniques: The book examines instances where there are multiple options for doing things, and make recommendations as to what is the "best" choice—or choices, as what is best often depends on the circumstances. Offers new procedures to update and explicate traditional techniques: The featured scholars present and explain new options for data analysis, discussing the advantages and disadvantages of the new procedures in depth, describing how to perform them, and demonstrating their use. Intended Audience: Representing the vanguard of research methods for the 21st century, this book is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource for practical and sound advice from leading experts in quantitative methods.