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| benefits of meta analysis: Cochrane Handbook for Systematic Reviews of Interventions Julian P. T. Higgins, Sally Green, 2008-11-24 Healthcare providers, consumers, researchers and policy makers are inundated with unmanageable amounts of information, including evidence from healthcare research. It has become impossible for all to have the time and resources to find, appraise and interpret this evidence and incorporate it into healthcare decisions. Cochrane Reviews respond to this challenge by identifying, appraising and synthesizing research-based evidence and presenting it in a standardized format, published in The Cochrane Library (www.thecochranelibrary.com). The Cochrane Handbook for Systematic Reviews of Interventions contains methodological guidance for the preparation and maintenance of Cochrane intervention reviews. Written in a clear and accessible format, it is the essential manual for all those preparing, maintaining and reading Cochrane reviews. Many of the principles and methods described here are appropriate for systematic reviews applied to other types of research and to systematic reviews of interventions undertaken by others. It is hoped therefore that this book will be invaluable to all those who want to understand the role of systematic reviews, critically appraise published reviews or perform reviews themselves. |
| benefits of meta analysis: Doing Meta-Analysis with R Mathias Harrer, Pim Cuijpers, Toshi A. Furukawa, David D. Ebert, 2021-09-15 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 |
| benefits of meta analysis: Handbook of Meta-Analysis Christopher H. Schmid, Theo Stijnen, Ian White, 2020-09-07 1. Provides a comprehensive overview of meta-analysis methods and applications. 2. Divided into four major sub-topics, covering univariate meta-analysis, multivariate, applications and policy. 3. Designed to be suitable for graduate students and researchers new to the field. 4. Includes lots of real examples, with data and software code made available. 5. Chapters written by the leading researchers in the field. |
| benefits of meta analysis: Systematic Reviews in Health Care Matthias Egger, George Davey-Smith, Douglas Altman, 2008-04-15 The second edition of this best-selling book has been thoroughly revised and expanded to reflect the significant changes and advances made in systematic reviewing. New features include discussion on the rationale, meta-analyses of prognostic and diagnostic studies and software, and the use of systematic reviews in practice. |
| benefits of meta analysis: The Handbook of Research Synthesis and Meta-Analysis Harris Cooper, Larry V. Hedges, Jeffrey C. Valentine, 2019-06-14 Research synthesis is the practice of systematically distilling and integrating data from many studies in order to draw more reliable conclusions about a given research issue. When the first edition of The Handbook of Research Synthesis and Meta-Analysis was published in 1994, it quickly became the definitive reference for conducting meta-analyses in both the social and behavioral sciences. In the third edition, editors Harris Cooper, Larry Hedges, and Jeff Valentine present updated versions of classic chapters and add new sections that evaluate cutting-edge developments in the field. The Handbook of Research Synthesis and Meta-Analysis draws upon groundbreaking advances that have transformed research synthesis from a narrative craft into an important scientific process in its own right. The editors and leading scholars guide the reader through every stage of the research synthesis process—problem formulation, literature search and evaluation, statistical integration, and report preparation. The Handbook incorporates state-of-the-art techniques from all quantitative synthesis traditions and distills a vast literature to explain the most effective solutions to the problems of quantitative data integration. Among the statistical issues addressed are the synthesis of non-independent data sets, fixed and random effects methods, the performance of sensitivity analyses and model assessments, the development of machine-based abstract screening, the increased use of meta-regression and the problems of missing data. The Handbook also addresses the non-statistical aspects of research synthesis, including searching the literature and developing schemes for gathering information from study reports. Those engaged in research synthesis will find useful advice on how tables, graphs, and narration can foster communication of the results of research syntheses. The third edition of the Handbook provides comprehensive instruction in the skills necessary to conduct research syntheses and represents the premier text on research synthesis. Praise for the first edition: The Handbook is a comprehensive treatment of literature synthesis and provides practical advice for anyone deep in the throes of, just teetering on the brink of, or attempting to decipher a meta-analysis. Given the expanding application and importance of literature synthesis, understanding both its strengths and weaknesses is essential for its practitioners and consumers. This volume is a good beginning for those who wish to gain that understanding. —Chance Meta-analysis, as the statistical analysis of a large collection of results from individual studies is called, has now achieved a status of respectability in medicine. This respectability, when combined with the slight hint of mystique that sometimes surrounds meta-analysis, ensures that results of studies that use it are treated with the respect they deserve....The Handbook of Research Synthesis is one of the most important publications in this subject both as a definitive reference book and a practical manual.—British Medical Journal When the first edition of The Handbook of Research Synthesis was published in 1994, it quickly became the definitive reference for researchers conducting meta-analyses of existing research in both the social and biological sciences. In this fully revised second edition, editors Harris Cooper, Larry Hedges, and Jeff Valentine present updated versions of the Handbook's classic chapters, as well as entirely new sections reporting on the most recent, cutting-edge developments in the field. Research synthesis is the practice of systematically distilling and integrating data from a variety of sources in order to draw more reliable conclusions about a given question or topic. The Handbook of Research Synthesis and Meta-Analysis draws upon years of groundbreaking advances that have transformed research synthesis from a narrative craft into an important scientific process in its own right. Cooper, Hedges, and Valentine have assembled leading authorities in the field to guide the reader through every stage of the research synthesis process—problem formulation, literature search and evaluation, statistical integration, and report preparation. The Handbook of Research Synthesis and Meta-Analysis incorporates state-of-the-art techniques from all quantitative synthesis traditions. Distilling a vast technical literature and many informal sources, the Handbook provides a portfolio of the most effective solutions to the problems of quantitative data integration. Among the statistical issues addressed by the authors are the synthesis of non-independent data sets, fixed and random effects methods, the performance of sensitivity analyses and model assessments, and the problem of missing data. The Handbook of Research Synthesis and Meta-Analysis also provides a rich treatment of the non-statistical aspects of research synthesis. Topics include searching the literature, and developing schemes for gathering information from study reports. Those engaged in research synthesis will also find useful advice on how tables, graphs, and narration can be used to provide the most meaningful communication of the results of research synthesis. In addition, the editors address the potentials and limitations of research synthesis, and its future directions. The past decade has been a period of enormous growth in the field of research synthesis. The second edition Handbook thoroughly revises original chapters to assure that the volume remains the most authoritative source of information for researchers undertaking meta-analysis today. In response to the increasing use of research synthesis in the formation of public policy, the second edition includes a new chapter on both the strengths and limitations of research synthesis in policy debates |
| benefits of meta analysis: Presenting Medical Statistics from Proposal to Publication Janet L. Peacock, Sally M. Kerry, Raymond R. Balise, 2017-07-21 As many medical and healthcare researchers have a love-hate relationship with statistics, the second edition of this practical reference book may make all the difference. Using practical examples, mainly from the authors' own research, the book explains how to make sense of statistics, turn statistical computer output into coherent information, and help decide which pieces of information to report and how to present them. The book takes you through all the stages of the research process, from the initial research proposal, through ethical approval and data analysis, to reporting on and publishing the findings. Helpful tips and information boxes, offer clear guidance throughout, including easily followed instructions on how to: -develop a quantitative research proposal for ethical/institutional approval or research funding -write up the statistical aspects of a paper for publication -choose and perform simple and more advanced statistical analyses -describe the statistical methods and present the results of an analysis. This new edition covers a wider range of statistical programs - SAS, STATA, R, and SPSS, and shows the commands needed to obtain the analyses and how to present it, whichever program you are using. Each specific example is annotated to indicate other scenarios that can be analysed using the same methods, allowing you to easily transpose the knowledge gained from the book to your own research. The principles of good presentation are also covered in detail, from translating relevant results into suitable extracts, through to randomised controlled trials, and how to present a meta-analysis. An added ingredient is the inclusion of code and datasets for all analyses shown in the book on our website (http://medical-statistics.info). Written by three experienced biostatisticians based in the UK and US, this is a step-by-step guide that will be invaluable to researchers and postgraduate students in medicine, those working in the professions allied to medicine, and statisticians in consultancy roles. |
| benefits of meta analysis: Finding What Works in Health Care Institute of Medicine, Board on Health Care Services, Committee on Standards for Systematic Reviews of Comparative Effectiveness Research, 2011-07-20 Healthcare decision makers in search of reliable information that compares health interventions increasingly turn to systematic reviews for the best summary of the evidence. Systematic reviews identify, select, assess, and synthesize the findings of similar but separate studies, and can help clarify what is known and not known about the potential benefits and harms of drugs, devices, and other healthcare services. Systematic reviews can be helpful for clinicians who want to integrate research findings into their daily practices, for patients to make well-informed choices about their own care, for professional medical societies and other organizations that develop clinical practice guidelines. Too often systematic reviews are of uncertain or poor quality. There are no universally accepted standards for developing systematic reviews leading to variability in how conflicts of interest and biases are handled, how evidence is appraised, and the overall scientific rigor of the process. In Finding What Works in Health Care the Institute of Medicine (IOM) recommends 21 standards for developing high-quality systematic reviews of comparative effectiveness research. The standards address the entire systematic review process from the initial steps of formulating the topic and building the review team to producing a detailed final report that synthesizes what the evidence shows and where knowledge gaps remain. Finding What Works in Health Care also proposes a framework for improving the quality of the science underpinning systematic reviews. This book will serve as a vital resource for both sponsors and producers of systematic reviews of comparative effectiveness research. |
| benefits of meta analysis: Modern Methods of Clinical Investigation Institute of Medicine, Committee on Technological Innovation in Medicine, 1990-02-01 The very rapid pace of advances in biomedical research promises us a wide range of new drugs, medical devices, and clinical procedures. The extent to which these discoveries will benefit the public, however, depends in large part on the methods we choose for developing and testing them. Modern Methods of Clinical Investigation focuses on strategies for clinical evaluation and their role in uncovering the actual benefits and risks of medical innovation. Essays explore differences in our current systems for evaluating drugs, medical devices, and clinical procedures; health insurance databases as a tool for assessing treatment outcomes; the role of the medical profession, the Food and Drug Administration, and industry in stimulating the use of evaluative methods; and more. This book will be of special interest to policymakers, regulators, executives in the medical industry, clinical researchers, and physicians. |
| benefits of meta analysis: Methods of Meta-Analysis John E Hunter, Frank L. Schmidt, 2004-04-07 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. |
| benefits of meta analysis: Systematic Reviews and Meta-Analysis Jacqueline Corcoran, Vijayan Pillai, 2008-02-13 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 book's glossary and handy checklists and sample search and data extraction forms maximize the boo'ks 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. |
| benefits of meta analysis: Meta-Analysis in Environmental Economics J.C. van den Bergh, Kenneth J. Button, Peter Nijkamp, G.C. Pepping, 2013-03-09 Meta-analysis is a formal synthesis of results and findings of scientific studies, which can assist in gaining new insights, explaining differences between results of similar studies, or determine useful directions of research. In this book we focus on the use of meta-analysis in environmental economics and related fields of study. The first part of the book covers the overall meta-approach methodology for social sciences and economics in particular. This is followed by technical and non-technical discussions of statistical and rough-set techniques for analysis. At appropriate places this is supplemented with reviews of applications in environmental economics and related fields. In the second part of the book a number of case studies show different aspects of the application of meta-analysis. The research areas considered include, among others, tourism multipliers, air pollution valuation, risk and value of life, pesticide price policy, travel time savings, and transport externality and policy issues. The benefits of the appropriate application of meta-analysis in environmental economics are a better use of existing information and knowledge, removal of some of the subjectivity from analysis and forecasting, and greater clarity as to where future efforts in environmental economic analysis can most gainfully be deployed. |
| benefits of meta analysis: Improving Learning Steve Higgins, 2019 Evidence-informed teaching is essential for effective teaching, but it is important to understand its limitations as well as its benefits. |
| benefits of meta analysis: Introduction to Meta-Analysis Michael Borenstein, Larry V. Hedges, Julian P. T. Higgins, Hannah R. Rothstein, 2011-08-24 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 |
| benefits of meta analysis: Meta-Study of Qualitative Health Research Barbara L. Paterson, 2001-06 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. |
| benefits of meta analysis: Introduction to the New Statistics Geoff Cumming, Robert Calin-Jageman, 2016-10-04 This is the first introductory statistics text to use an estimation approach from the start to help readers understand effect sizes, confidence intervals (CIs), and meta-analysis (‘the new statistics’). It is also the first text to explain the new and exciting Open Science practices, which encourage replication and enhance the trustworthiness of research. In addition, the book explains NHST fully so students can understand published research. Numerous real research examples are used throughout. The book uses today’s most effective learning strategies and promotes critical thinking, comprehension, and retention, to deepen users’ understanding of statistics and modern research methods. The free ESCI (Exploratory Software for Confidence Intervals) software makes concepts visually vivid, and provides calculation and graphing facilities. The book can be used with or without ESCI. Other highlights include: - Coverage of both estimation and NHST approaches, and how to easily translate between the two. - Some exercises use ESCI to analyze data and create graphs including CIs, for best understanding of estimation methods. -Videos of the authors describing key concepts and demonstrating use of ESCI provide an engaging learning tool for traditional or flipped classrooms. -In-chapter exercises and quizzes with related commentary allow students to learn by doing, and to monitor their progress. -End-of-chapter exercises and commentary, many using real data, give practice for using the new statistics to analyze data, as well as for applying research judgment in realistic contexts. -Don’t fool yourself tips help students avoid common errors. -Red Flags highlight the meaning of significance and what p values actually mean. -Chapter outlines, defined key terms, sidebars of key points, and summarized take-home messages provide a study tool at exam time. -http://www.routledge.com/cw/cumming offers for students: ESCI downloads; data sets; key term flashcards; tips for using SPSS for analyzing data; and videos. For instructors it offers: tips for teaching the new statistics and Open Science; additional homework exercises; assessment items; answer keys for homework and assessment items; and downloadable text images; and PowerPoint lecture slides. Intended for introduction to statistics, data analysis, or quantitative methods courses in psychology, education, and other social and health sciences, researchers interested in understanding the new statistics will also appreciate this book. No familiarity with introductory statistics is assumed. |
| benefits of meta analysis: Individual Participant Data Meta-Analysis Richard D. Riley, Jayne F. Tierney, Lesley A. Stewart, 2021-06-08 Individual Participant Data Meta-Analysis: A Handbook for Healthcare Research provides a comprehensive introduction to the fundamental principles and methods that healthcare researchers need when considering, conducting or using individual participant data (IPD) meta-analysis projects. Written and edited by researchers with substantial experience in the field, the book details key concepts and practical guidance for each stage of an IPD meta-analysis project, alongside illustrated examples and summary learning points. Split into five parts, the book chapters take the reader through the journey from initiating and planning IPD projects to obtaining, checking, and meta-analysing IPD, and appraising and reporting findings. The book initially focuses on the synthesis of IPD from randomised trials to evaluate treatment effects, including the evaluation of participant-level effect modifiers (treatment-covariate interactions). Detailed extension is then made to specialist topics such as diagnostic test accuracy, prognostic factors, risk prediction models, and advanced statistical topics such as multivariate and network meta-analysis, power calculations, and missing data. Intended for a broad audience, the book will enable the reader to: Understand the advantages of the IPD approach and decide when it is needed over a conventional systematic review Recognise the scope, resources and challenges of IPD meta-analysis projects Appreciate the importance of a multi-disciplinary project team and close collaboration with the original study investigators Understand how to obtain, check, manage and harmonise IPD from multiple studies Examine risk of bias (quality) of IPD and minimise potential biases throughout the project Understand fundamental statistical methods for IPD meta-analysis, including two-stage and one-stage approaches (and their differences), and statistical software to implement them Clearly report and disseminate IPD meta-analyses to inform policy, practice and future research Critically appraise existing IPD meta-analysis projects Address specialist topics such as effect modification, multiple correlated outcomes, multiple treatment comparisons, non-linear relationships, test accuracy at multiple thresholds, multiple imputation, and developing and validating clinical prediction models Detailed examples and case studies are provided throughout. |
| benefits of meta analysis: Advances in Meta-Analysis Terri Pigott, 2012-01-31 The subject of the book is advanced statistical analyses for quantitative research synthesis (meta-analysis), and selected practical issues relating to research synthesis that are not covered in detail in the many existing introductory books on research synthesis (or meta-analysis). Complex statistical issues are arising more frequently as the primary research that is summarized in quantitative syntheses itself becomes more complex, and as researchers who are conducting meta-analyses become more ambitious in the questions they wish to address. Also as researchers have gained more experience in conducting research syntheses, several key issues have persisted and now appear fundamental to the enterprise of summarizing research. Specifically the book describes multivariate analyses for several indices commonly used in meta-analysis (e.g., correlations, effect sizes, proportions and/or odds ratios), will outline how to do power analysis for meta-analysis (again for each of the different kinds of study outcome indices), and examines issues around research quality and research design and their roles in synthesis. For each of the statistical topics we will examine the different possible statistical models (i.e., fixed, random, and mixed models) that could be adopted by a researcher. In dealing with the issues of study quality and research design it covers a number of specific topics that are of broad concern to research synthesists. In many fields a current issue is how to make sense of results when studies using several different designs appear in a research literature (e.g., Morris & Deshon, 1997, 2002). In education and other social sciences a critical aspect of this issue is how one might incorporate qualitative (e.g., case study) research within a synthesis. In medicine, related issues concern whether and how to summarize observational studies, and whether they should be combined with randomized controlled trials (or even if they should be combined at all). For each topic, included is a worked example (e.g., for the statistical analyses) and/or a detailed description of a published research synthesis that deals with the practical (non-statistical) issues covered. |
| benefits of meta analysis: Statistical Methods for Meta-Analysis Larry V. Hedges, Ingram Olkin, 2014-06-28 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. |
| benefits of meta analysis: Meta-Analysis John Edward Hunter, Frank L. Schmidt, Gregg B. Jackson, 1982-10 There are few areas of modern life that are burdened by as much information and advice, often contradictory, as our diet and health: eat a lot of meat, eat no meat; whole-grains are healthy, whole-grains are a disaster; eat everything in moderation; eat only certain foods--and on and on. In One Hundred Million Years of Food biological anthropologist Stephen Le explains how cuisines of different cultures are a result of centuries of evolution, finely tuned to our biology and surroundings. Today many cultures have strayed from their ancestral diets, relying instead on mass-produced food often made with chemicals that may be contributing to a rise in so-called Western diseases, such as cancer, heart disease, and obesity. Travelling around the world to places as far-flung as Vietnam, Kenya, India, and the US, Stephen Le introduces us to people who are growing, cooking, and eating food using both traditional and modern methods, striving for a sustainable, healthy diet. In clear, compelling arguments based on scientific research, Le contends that our ancestral diets provide the best first line of defense in protecting our health and providing a balanced diet. Fast-food diets, as well as strict regimens like paleo or vegan, in effect highjack our biology and ignore the complex nature of our bodies. In One Hundred Million Years of Food Le takes us on a guided tour of evolution, demonstrating how our diets are the result of millions of years of history, and how we can return to a sustainable, healthier way of eating.--Publisher's description. |
| benefits of meta analysis: Handbook of Meta-analysis in Ecology and Evolution Julia Koricheva, Jessica Gurevitch, Kerrie Mengersen, 2013-04-21 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 |
| benefits of meta analysis: Meta-Analysis with R Guido Schwarzer, James R. Carpenter, Gerta Rücker, 2015-10-08 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. |
| benefits of meta analysis: Meta-Analytic Procedures for Social Research Robert Rosenthal, 1991-05 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. |
| benefits of meta analysis: Oxford Textbook of Public Health , 2002 |
| benefits of meta analysis: Methods for Meta-Analysis in Medical Research A. J. Sutton, 2000-12-19 Major text including chapters on the following: defining outcome measures; assessing heterogeneity; using fixed effects methods and random effects models for combining study estimates; publication bias. |
| benefits of meta analysis: Handbook of Applied Multivariate Statistics and Mathematical Modeling Howard E.A. Tinsley, Steven D. Brown, 2000-05-22 Multivariate statistics and mathematical models provide flexible and powerful tools essential in most disciplines. Nevertheless, many practicing researchers lack an adequate knowledge of these techniques, or did once know the techniques, but have not been able to keep abreast of new developments. The Handbook of Applied Multivariate Statistics and Mathematical Modeling explains the appropriate uses of multivariate procedures and mathematical modeling techniques, and prescribe practices that enable applied researchers to use these procedures effectively without needing to concern themselves with the mathematical basis. The Handbook emphasizes using models and statistics as tools. The objective of the book is to inform readers about which tool to use to accomplish which task. Each chapter begins with a discussion of what kinds of questions a particular technique can and cannot answer. As multivariate statistics and modeling techniques are useful across disciplines, these examples include issues of concern in biological and social sciences as well as the humanities. |
| benefits of meta analysis: An Introduction to Systematic Reviews David Gough, Sandy Oliver, James Thomas, 2012-03-22 This timely, engaging book provides an overview of the nature, logic, diversity and process of undertaking systematic reviews as part of evidence informed decision making. A focused, accessible and technically up-to-date book, it covers the full breadth of approaches to reviews from statistical meta analysis to meta ethnography. It is ideal for anyone undertaking their own systematic review - providing all the necessary conceptual and technical background needed to make a good start on the process. The content is divided into five clear sections: • Approaches to reviewing • Getting started • Gathering and describing research • Appraising and synthesising data • Making use of reviews/models of research use. Easy to read and logically structured, this book is essential reading for anyone doing systematic reviews. David Gough is Professor of Evidence Informed Policy and Practice and Director of SSRU and its EPPI-Centre and Co-Editor of the journal Evidence & Policy. Sandy Oliver is Professor of Public Policy and Deputy Director of SSRU and its EPPI-Centre. James Thomas is Reader in Social Policy, Assistant Director of SSRU and Associate Direcctor of the EPPI-Centre. |
| benefits of meta analysis: Evidence Synthesis and Meta-analysis for Drug Safety Council for International Organizations of Medical Sciences (CIOMS), Council for International Organizations of Medical Sciences. Working Group X, 2016 At any point in the drug development process, systematic reviews and meta-analysis can provide important information to guide the future path of the development program and any actions that might be needed in the post-marketing setting. This report gives the rationale for why and when a meta-analysis should be considered, all in the context of regulatory decision-making, and the tasks, data collection, and analyses that need to be carried out to inform those decisions. There is increasing demand by decision-makers in health care, the bio-pharmaceutical industry, and society at large to have access to the best available evidence on benefits and risks of medicinal products. The best strategy will take an overview of all the evidence and where it is possible and sensible, combine the evidence and summarize the results. For efficacy, the outcomes generally use the same or very similar predefined events for each of the trials to be included. Most regulatory guidance and many Cochrane Collaboration reviews have usually given more attention to assessment of benefits, while issues around combining evidence on harms have not been as well-covered. However, the (inevitably) unplanned nature of the data on safety makes the process more difficult. Combining evidence on adverse events (AEs), where these were not the focus of the original studies, is more challenging than combining evidence on pre-specified benefits. This focus on AEs represents the main contribution of the current CIOMS X report. The goal of the CIOMS X report is to provide principles on appropriate application of meta-analysis in assessing safety of pharmaceutical products to inform regulatory decision-making. This report is about meta-analysis in this narrow area, but the present report should also provide conceptually helpful points to consider for a wider range of applications, such as vaccines, medical devices, veterinary medicines or even products that are combinations of medicinal products and medical devices. Although some of the content of this report describes highly technical statistical concepts and methods (in particular Chapter 4), the ambition of the working group has been to make it comprehensible to non-statisticians for its use in clinical epidemiology and regulatory science. To that end, Chapters 3 and 4, which contain the main technical statistical aspects of the appropriate design, analysis and reporting of a meta-analysis of safety data are followed by Chapter 5 with a thought process for evaluating the findings of a meta-analysis and how to communicate these. |
| benefits of meta analysis: Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide Agency for Health Care Research and Quality (U.S.), 2013-02-21 This User’s Guide is a resource for investigators and stakeholders who develop and review observational comparative effectiveness research protocols. It explains how to (1) identify key considerations and best practices for research design; (2) build a protocol based on these standards and best practices; and (3) judge the adequacy and completeness of a protocol. Eleven chapters cover all aspects of research design, including: developing study objectives, defining and refining study questions, addressing the heterogeneity of treatment effect, characterizing exposure, selecting a comparator, defining and measuring outcomes, and identifying optimal data sources. Checklists of guidance and key considerations for protocols are provided at the end of each chapter. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews. More more information, please consult the Agency website: www.effectivehealthcare.ahrq.gov) |
| benefits of meta analysis: Biostatistics for Medical and Biomedical Practitioners Julien I. E. Hoffman, 2015-09-03 Biostatistics for Practitioners: An Interpretative Guide for Medicine and Biology deals with several aspects of statistics that are indispensable for researchers and students across the biomedical sciences. The book features a step-by-step approach, focusing on standard statistical tests, as well as discussions of the most common errors. The book is based on the author's 40+ years of teaching statistics to medical fellows and biomedical researchers across a wide range of fields. - Discusses how to use the standard statistical tests in the biomedical field, as well as how to make statistical inferences (t test, ANOVA, regression etc.) - Includes non-standards tests, including equivalence or non-inferiority testing, extreme value statistics, cross-over tests, and simple time series procedures such as the runs test and Cusums - Introduces procedures such as multiple regression, Poisson regression, meta-analysis and resampling statistics, and provides references for further studies |
| benefits of meta analysis: Network Meta-Analysis for Decision-Making Sofia Dias, A. E. Ades, Nicky J. Welton, Jeroen P. Jansen, Alexander J. Sutton, 2018-03-19 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. |
| benefits of meta analysis: Publication Bias in Meta-Analysis Hannah R. Rothstein, Alexander J. Sutton, Michael Borenstein, 2005-11-18 Publication bias is the tendency to decide to publish a study based on the results of the study, rather than on the basis of its theoretical or methodological quality. It can arise from selective publication of favorable results, or of statistically significant results. This threatens the validity of conclusions drawn from reviews of published scientific research. Meta-analysis is now used in numerous scientific disciplines, summarizing quantitative evidence from multiple studies. If the literature being synthesised has been affected by publication bias, this in turn biases the meta-analytic results, potentially producing overstated conclusions. Publication Bias in Meta-Analysis examines the different types of publication bias, and presents the methods for estimating and reducing publication bias, or eliminating it altogether. Written by leading experts, adopting a practical and multidisciplinary approach. Provides comprehensive coverage of the topic including: Different types of publication bias, Mechanisms that may induce them, Empirical evidence for their existence, Statistical methods to address them, Ways in which they can be avoided. Features worked examples and common data sets throughout. Explains and compares all available software used for analysing and reducing publication bias. Accompanied by a website featuring software, data sets and further material. Publication Bias in Meta-Analysis adopts an inter-disciplinary approach and will make an excellent reference volume for any researchers and graduate students who conduct systematic reviews or meta-analyses. University and medical libraries, as well as pharmaceutical companies and government regulatory agencies, will also find this invaluable. |
| benefits of meta analysis: Meta-Analysis Mike W.-L. Cheung, 2015-05-06 Presents a novel approach to conducting meta-analysis using structural equation modeling. Structural equation modeling (SEM) and meta-analysis are two powerful statistical methods in the educational, social, behavioral, and medical sciences. They are often treated as two unrelated topics in the literature. This book presents a unified framework on analyzing meta-analytic data within the SEM framework, and illustrates how to conduct meta-analysis using the metaSEM package in the R statistical environment. Meta-Analysis: A Structural Equation Modeling Approach begins by introducing the importance of SEM and meta-analysis in answering research questions. Key ideas in meta-analysis and SEM are briefly reviewed, and various meta-analytic models are then introduced and linked to the SEM framework. Fixed-, random-, and mixed-effects models in univariate and multivariate meta-analyses, three-level meta-analysis, and meta-analytic structural equation modeling, are introduced. Advanced topics, such as using restricted maximum likelihood estimation method and handling missing covariates, are also covered. Readers will learn a single framework to apply both meta-analysis and SEM. Examples in R and in Mplus are included. This book will be a valuable resource for statistical and academic researchers and graduate students carrying out meta-analyses, and will also be useful to researchers and statisticians using SEM in biostatistics. Basic knowledge of either SEM or meta-analysis will be helpful in understanding the materials in this book. |
| benefits of meta analysis: Oral Epidemiology Marco A. Peres, Jose Leopoldo Ferreira Antunes, Richard G. Watt, 2020-10-19 This intermediate textbook on oral epidemiology is designed to meet the needs of advanced students in the fields of Dentistry and Oral Health and dentists in the early stages of their career. Readers will find detailed information on the epidemiology of individual diseases and disorders and on hot topics and methods in oral health research. The extensive first part of the book explores the international epidemiological literature regarding a wide range of conditions, from dental caries and periodontal diseases to halitosis and malocclusions. In each case, the prevalence, disease-specific measures, and associated factors are identified. Attention is then focused on cutting-edge research topics in oral epidemiology, such as the intriguing mechanisms linking oral diseases and chronic general diseases, life course epidemiology, and the role of socioeconomic determinants of oral health. The final part of the book is devoted to description of the epidemiological methods and tools applied in the field of oral health. Here, the coverage includes validation of questionnaires, data collection and data analyses, and systematic reviews and meta-analyses. |
| benefits of meta analysis: Sharing Clinical Trial Data Institute of Medicine, Board on Health Sciences Policy, Committee on Strategies for Responsible Sharing of Clinical Trial Data, 2015-04-20 Data sharing can accelerate new discoveries by avoiding duplicative trials, stimulating new ideas for research, and enabling the maximal scientific knowledge and benefits to be gained from the efforts of clinical trial participants and investigators. At the same time, sharing clinical trial data presents risks, burdens, and challenges. These include the need to protect the privacy and honor the consent of clinical trial participants; safeguard the legitimate economic interests of sponsors; and guard against invalid secondary analyses, which could undermine trust in clinical trials or otherwise harm public health. Sharing Clinical Trial Data presents activities and strategies for the responsible sharing of clinical trial data. With the goal of increasing scientific knowledge to lead to better therapies for patients, this book identifies guiding principles and makes recommendations to maximize the benefits and minimize risks. This report offers guidance on the types of clinical trial data available at different points in the process, the points in the process at which each type of data should be shared, methods for sharing data, what groups should have access to data, and future knowledge and infrastructure needs. Responsible sharing of clinical trial data will allow other investigators to replicate published findings and carry out additional analyses, strengthen the evidence base for regulatory and clinical decisions, and increase the scientific knowledge gained from investments by the funders of clinical trials. The recommendations of Sharing Clinical Trial Data will be useful both now and well into the future as improved sharing of data leads to a stronger evidence base for treatment. This book will be of interest to stakeholders across the spectrum of research-from funders, to researchers, to journals, to physicians, and ultimately, to patients. |
| benefits of meta analysis: Medical Eligibility Criteria for Contraceptive Use , 2010 Medical Eligibility Criteria for Contraceptive Use reviews the medical eligibility criteria for use of contraception, offering guidance on the safety and use of different methods for women and men with specific characteristics or known medical conditions. The recommendations are based on systematic reviews of available clinical and epidemiological research. It is a companion guideline to Selected Practice Recommendations for Contraceptive Use. Together, these documents are intended to be used by policy-makers, program managers, and the scientific community to support national programs in the preparation of service delivery guidelines. The fourth edition of this useful resource supersedes previous editions, and has been fully updated and expanded. It includes over 86 new recommendations and 165 updates to recommendations in the previous edition. Guidance for populations with special needs is now provided, and a new annex details evidence on drug interactions from concomitant use of antiretroviral therapies and hormonal contraceptives. To assist users familiar with the third edition, new and updated recommendations are highlighted. Everyone involved in providing family planning services and contraception should have the fourth edition of Medical Eligibility Criteria for Contraceptive Use at hand. |
| benefits of meta analysis: Group Performance Bernard A. Nijstad, 2009-06-22 People interact and perform in group settings in all areas of life. Organizations and businesses are increasingly structuring work around groups and teams. Every day, we work in groups such as families, friendship groups, societies and sports teams, to make decisions and plans, solve problems, perform physical tasks, generate creative ideas, and more. Group Performance outlines the current state of social psychological theories and findings concerning the performance of groups. It explores the basic theories surrounding group interaction and development and investigates how groups affect their members. Bernard A. Nijstad discusses these issues in relation to the many different tasks that groups may perform, including physical tasks, idea generation and brainstorming, decision-making, problem-solving, and making judgments and estimates. Finally, the book closes with an in-depth discussion of teamwork and the context in which groups interact and perform. Offering an integrated approach, with particular emphasis on the interplay between group members, the group task, interaction processes and context, this book provides a state-of-the-art overview of social psychological theory and research. It will be highly valuable to undergraduates, graduates and researchers in social psychology, organizational behavior and business. |
| benefits of meta analysis: Meta-Analysis Fredric M. Wolf, Fredric Marc Wolf, 1986-04 Meta-Analysis shows concisely, yet comprehensively, how to apply statistical methods to achieve a literature review of a common research domain. It demonstrates the use of combined tests and measures of effect size to synthesize quantitatively the results of independent studies for both group differences and correlations. Strengths and weaknesses of alternative approaches, as well as of meta-analysis in general, are presented. |
| benefits of meta analysis: Users' Guides to the Medical Literature Gordon Guyatt, Drummond Rennie, Maureen O. Meade, Deborah J. Cook, 2008-03-01 The “essential” companion to the landmark Users' Guides to the Medical Literature - completely revised and updated! 5 STAR DOODY'S REVIEW! This second edition is even better than the original. Information is easier to find and the additional resources that will be available at www.JAMAevidence.com will provide readers with a one-stop source for evidence-based medicine.--Doody's Review Service Evidence-based medicine involves the careful interpretation of medical studies and its clinical application. And no resource helps you do it better-and faster-than Users' Guides to the Medical Literature: Essentials of Evidence-Based Clinical Practice. This streamlined reference distills the most clinically-relevant coverage from the parent Users' Guide Manual into one highly-focused, portable resource. Praised for its clear explanations of detailed statistical and mathematical principles, The Essentials concisely covers all the basic concepts of evidence-based medicine--everything you need to deliver optimal patient care. It's a perfect at-a-glance source for busy clinicians and students, helping you distinguish between solid medical evidence and poor medical evidence, tailor evidence-based medicine for each patient, and much more. Now in its second edition, this carry-along quick reference is more clinically relevant--and more essential--than ever! FEATURES Completely revised and updated with all new coverage of the basic issues in evidence-based medicine in patient care Abundant real-world examples drawn from the medical literature are woven throughout, and include important related principles and pitfalls in using clinical research in patient care decisions Edited by over 60 internationally recognized editors and contributors from around the globe Also look for JAMAevidence.com, a new interactive database for the best practice of evidence based medicine. |
| benefits of meta analysis: Physical Activity and Cancer Kerry S. Courneya, Christine M. Friedenreich, 2010-11-26 This book explores in depth the relation between physical activity and cancer control, including primary prevention, coping with treatments, recovery after treatments, long-term survivorship, secondary prevention, and survival. The first part of the book presents the most recent research on the impact of physical activity in preventing a range of cancers. In the second part, the association between physical activity and cancer survivorship is addressed. The effects of physical activity on supportive care endpoints (e.g., quality of life, fatigue, physical functioning) and disease endpoints (e.g., biomarkers, recurrence, survival) are carefully analyzed. In addition, the determinants of physical activity in cancer survivors are discussed, and behavior change strategies for increasing physical activity in cancer survivors are appraised. The final part of the book is devoted to special topics, including the relation of physical activity to pediatric cancer survivorship and to palliative cancer care. |
| benefits of meta analysis: Meta-Analysis, Decision Analysis, and Cost-Effectiveness Analysis Diana B. Petitti, 2000 Public health and in health policy courses at the undergraduate and graduate level. |
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