Introduction to Meta-Analysis

Author: Michael Borenstein,Larry V. Hedges,Julian P. T. Higgins,Hannah R. Rothstein

Publisher: John Wiley & Sons

ISBN: 1119964377

Category: Medical

Page: 450

View: 6198

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

Introduction to Meta-Analysis

Author: CTI Reviews

Publisher: Cram101 Textbook Reviews

ISBN: 1467254916

Category: Education

Page: 34

View: 8615

Facts101 is your complete guide to Introduction to Meta-Analysis. In this book, you will learn topics such as as those in your book plus much more. With key features such as key terms, people and places, Facts101 gives you all the information you need to prepare for your next exam. Our practice tests are specific to the textbook and we have designed tools to make the most of your limited study time.

Statistical Meta-Analysis with Applications

Author: Joachim Hartung,Guido Knapp,Bimal K. Sinha

Publisher: John Wiley & Sons

ISBN: 1118210964

Category: Medical

Page: 248

View: 7298

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.

The Essential Guide to Effect Sizes

Statistical Power, Meta-Analysis, and the Interpretation of Research Results

Author: Paul D. Ellis

Publisher: Cambridge University Press

ISBN: 0521142466

Category: Business & Economics

Page: 173

View: 6082

A jargon-free introduction for students and researchers looking to interpret the practical significance of their results.

Network Meta-Analysis for Decision-Making

Author: Sofia Dias,A. E. Ades,Nicky J. Welton,Jeroen P. Jansen,Alexander J. Sutton

Publisher: John Wiley & Sons

ISBN: 1118951727

Category: Mathematics

Page: 488

View: 1963

A practical guide to network meta-analysis with examples and code In the evaluation of healthcare, rigorous methods of quantitative assessment are necessary to establish which interventions are effective and cost-effective. Often a single study will not provide the answers and it is desirable to synthesise evidence from multiple sources, usually randomised controlled trials. This book takes an approach to evidence synthesis that is specifically intended for decision making when there are two or more treatment alternatives being evaluated, and assumes that the purpose of every synthesis is to answer the question “for this pre-identified population of patients, which treatment is ‘best’?” A comprehensive, coherent framework for network meta-analysis (mixed treatment comparisons) is adopted and estimated using Bayesian Markov Chain Monte Carlo methods implemented in the freely available software WinBUGS. Each chapter contains worked examples, exercises, solutions and code that may be adapted by readers to apply to their own analyses. This book can be used as an introduction to evidence synthesis and network meta-analysis, its key properties and policy implications. Examples and advanced methods are also presented for the more experienced reader. Methods used throughout this book can be applied consistently: model critique and checking for evidence consistency are emphasised. Methods are based on technical support documents produced for NICE Decision Support Unit, which support the NICE Methods of Technology Appraisal. Code presented is also the basis for the code used by the ISPOR Task Force on Indirect Comparisons. Includes extensive carefully worked examples, with thorough explanations of how to set out data for use in WinBUGS and how to interpret the output. Network Meta-Analysis for Decision Making will be of interest to decision makers, medical statisticians, health economists, and anyone involved in Health Technology Assessment including the pharmaceutical industry.

Advanced BASIC Meta-analysis

Author: Brian Mullen

Publisher: Psychology Press

ISBN: 9780805805024

Category: Psychology

Page: 169

View: 1474

In response to the growing emphasis on precision in the summarization and integration of research literature, Advanced BASIC Meta-Analysis presents an overview of strategies, techniques, and procedures used in meta-analysis. The book and software provide an integrated and comprehensive combination of meta-analytic tools for the statistical integration of independent study results. Advanced BASIC Meta-Analysis has three distinct goals: * to provide a clear and user-friendly introduction to the procedures and rules of effective meta-analytic integration; * to present the implicit assumptions and strategies that guide successful meta-analytic integrations; and * to develop a meta-analytic database management system that allows users to create, modify, and update a database, including the relevant statistical information and predictors, for a given research domain. The companion software system allows users to perform a full complement of meta-analytic statistical functions with the speed and flexibility of a database management system. It can also construct a wide array of meta-analytic graphic displays. This text and software package serves as a useful introduction to the quantitative assessment of research domains for those new to meta-analyses. It is also a valuable sourcebook for those who have already conducted meta-analyses.

Applied Meta-analysis for Social Science Research

Author: Noel A. Card

Publisher: Guilford Press

ISBN: 1609184998

Category: Psychology

Page: 377

View: 3993

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.

Meta-Analysis with R

Author: Guido Schwarzer,James R. Carpenter,Gerta Rücker

Publisher: Springer

ISBN: 3319214160

Category: Medical

Page: 252

View: 4308

This book provides a comprehensive introduction to performing meta-analysis using the statistical software R. It is intended for quantitative researchers and students in the medical and social sciences who wish to learn how to perform meta-analysis with R. As such, the book introduces the key concepts and models used in meta-analysis. It also includes chapters on the following advanced topics: publication bias and small study effects; missing data; multivariate meta-analysis, network meta-analysis; and meta-analysis of diagnostic studies.

Meta-Analytic Structural Equation Modelling

Author: Suzanne Jak

Publisher: Springer

ISBN: 3319271741

Category: Mathematics

Page: 88

View: 5564

This book explains how to employ MASEM, the combination of meta-analysis (MA) and structural equation modelling (SEM). It shows how by using MASEM, a single model can be tested to explain the relationships between a set of variables in several studies. This book gives an introduction to MASEM, with a focus on the state of the art approach: the two stage approach of Cheung and Cheung & Chan. Both, the fixed and the random approach to MASEM are illustrated with two applications to real data. All steps that have to be taken to perform the analyses are discussed extensively. All data and syntax files are available online, so that readers can imitate all analyses. By using SEM for meta-analysis, this book shows how to benefit from all available information from all available studies, even if few or none of the studies report about all relationships that feature in the full model of interest.

Introduction to Research - E-Book

Understanding and Applying Multiple Strategies

Author: Elizabeth DePoy,Laura N. Gitlin

Publisher: Elsevier Health Sciences

ISBN: 0323291074

Category: Medical

Page: 384

View: 7412

Bridge the gap between research and practice with DePoy and Gitlin's Introduction to Research: Understanding and Applying Multiple Strategies, 4th Edition. This completely updated, user-friendly text helps you better understand not only the research process, but also research designs and their applications to the real world of clinical practice. Covering multiple research strategies (including both qualitative and quantitative research), it gives you a balanced approach to various research traditions, addressing emerging key issues in today's health care environment. Offers a balanced approach to various research methods and multiple research strategies, including qualitative, quantitative, naturalistic and experimental-type, and more. Presents complex information in a clear, highly readable, and easy-to-understand manner. Keeps information relevant to today's health care environment with real-world "snapshots" and a final Stories from the Field chapter. Includes detailed discussions of qualitative and quantitative methodologies, a unique and balanced focus that makes this text more comprehensive than others in its field. Covers experimental-type, naturalistic, and mixed method design strategies, improving your ability to compare, contrast, and integrate different methods. Evolve online resources include statistics math tips to accompany Chapter 19, crossword puzzles, useful weblinks, and sample forms. Reflects recent changes in the field, including new material on preparing poster presentations, community and participatory research, translation issues, and advanced scale development, giving you the tools you need to devise successful research studies. Includes expanded evidence-based material and occupational therapy-specific information, discussing the methods used in each study.

Leadership and Organizational Outcomes

Meta-Analysis of Empirical Studies

Author: Engin Karadağ

Publisher: Springer

ISBN: 3319149083

Category: Business & Economics

Page: 273

View: 9003

This book focuses on the effect of leadership on organizational outcomes and summarizes the current research findings in the field. It addresses the need for inclusive and interpretive studies in the field in order to interpret leadership literature and suggest new pathways for further studies. Appropriately, a meta-analysis approach is used by the contributors to show the big picture to the researchers by analyzing and combining the findings from different independent studies. In particular, the editors compile various studies examining the relationship between the leadership and thirteen organizational outcomes separately. The philosophy behind this book is to direct future research and practices rather than addressing the limits of current studies.

Introduction to Mixed Modelling

Beyond Regression and Analysis of Variance

Author: N. W. Galwey

Publisher: John Wiley & Sons

ISBN: 1118861825

Category: Mathematics

Page: 504

View: 2239

Mixed modelling is very useful, and easier than you think! Mixed modelling is now well established as a powerful approach to statistical data analysis. It is based on the recognition of random-effect terms in statistical models, leading to inferences and estimates that have much wider applicability and are more realistic than those otherwise obtained. Introduction to Mixed Modelling leads the reader into mixed modelling as a natural extension of two more familiar methods, regression analysis and analysis of variance. It provides practical guidance combined with a clear explanation of the underlying concepts. Like the first edition, this new edition shows diverse applications of mixed models, provides guidance on the identification of random-effect terms, and explains how to obtain and interpret best linear unbiased predictors (BLUPs). It also introduces several important new topics, including the following: Use of the software SAS, in addition to GenStat and R. Meta-analysis and the multiple testing problem. The Bayesian interpretation of mixed models. Including numerous practical exercises with solutions, this book provides an ideal introduction to mixed modelling for final year undergraduate students, postgraduate students and professional researchers. It will appeal to readers from a wide range of scientific disciplines including statistics, biology, bioinformatics, medicine, agriculture, engineering, economics, archaeology and geography. Praise for the first edition: “One of the main strengths of the text is the bridge it provides between traditional analysis of variance and regression models and the more recently developed class of mixed models...Each chapter is well-motivated by at least one carefully chosen example...demonstrating the broad applicability of mixed models in many different disciplines...most readers will likely learn something new, and those previously unfamiliar with mixed models will obtain a solid foundation on this topic.”—Kerrie Nelson University of South Carolina, in American Statistician, 2007

Best Practices in Quantitative Methods

Author: Jason W. Osborne

Publisher: SAGE

ISBN: 1412940656

Category: Social Science

Page: 596

View: 6826

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.

Test-Driven Development

An Empirical Evaluation of Agile Practice

Author: Lech Madeyski

Publisher: Springer Science & Business Media

ISBN: 9783642042881

Category: Computers

Page: 245

View: 9452

Agile methods are gaining more and more interest both in industry and in research. Many industries are transforming their way of working from traditional waterfall projects with long duration to more incremental, iterative and agile practices. At the same time, the need to evaluate and to obtain evidence for different processes, methods and tools has been emphasized. Lech Madeyski offers the first in-depth evaluation of agile methods. He presents in detail the results of three different experiments, including concrete examples of how to conduct statistical analysis with meta analysis or the SPSS package, using as evaluation indicators the number of acceptance tests passed (overall and per hour) and design complexity metrics. The book is appropriate for graduate students, researchers and advanced professionals in software engineering. It proves the real benefits of agile software development, provides readers with in-depth insights into experimental methods in the context of agile development, and discusses various validity threats in empirical studies.

Methods of Meta-Analysis

Correcting Error and Bias in Research Findings

Author: John E Hunter,Frank L. Schmidt

Publisher: SAGE

ISBN: 9781412904797

Category: Psychology

Page: 582

View: 7181

Meta-analysis is arguably the most important methodological innovation in the social and behavioral sciences in the last 25 years. Developed to offer researchers an informative account of which methods are most useful in integrating research findings across studies, this book will enable the reader to apply, as well as understand, meta-analytic methods. Rather than taking an encyclopedic approach, the authors have focused on carefully developing those techniques that are most applicable to social science research, and have given a general conceptual description of more complex and rarely-used techniques. Fully revised and updated, Methods of Meta-Analysis, Second Edition is the most comprehensive text on meta-analysis available today.