Download or read book Applications of Estimating Treatment Effects in Meta analyses with Missing Data written by Isabel Elaine Allen and published by . This book was released on 2000 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Developing a Protocol for Observational Comparative Effectiveness Research A User s Guide written by Agency for Health Care Research and Quality (U.S.) and published by Government Printing Office. This book was released on 2013-02-21 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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)

Download or read book Cochrane Handbook for Systematic Reviews of Interventions written by Julian P. T. Higgins and published by Wiley. This book was released on 2008-11-24 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Applied Meta Analysis with R and Stata written by Ding-Geng (Din) Chen and published by CRC Press. This book was released on 2021-03-30 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Applied Meta Analysis with R written by Ding-Geng (Din) Chen and published by CRC Press. This book was released on 2013-05-03 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Handbook of Missing Data Methodology written by Geert Molenberghs and published by CRC Press. This book was released on 2014-11-06 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: Missing data affect nearly every discipline by complicating the statistical analysis of collected data. But since the 1990s, there have been important developments in the statistical methodology for handling missing data. Written by renowned statisticians in this area, Handbook of Missing Data Methodology presents many methodological advances and the latest applications of missing data methods in empirical research. Divided into six parts, the handbook begins by establishing notation and terminology. It reviews the general taxonomy of missing data mechanisms and their implications for analysis and offers a historical perspective on early methods for handling missing data. The following three parts cover various inference paradigms when data are missing, including likelihood and Bayesian methods; semi-parametric methods, with particular emphasis on inverse probability weighting; and multiple imputation methods. The next part of the book focuses on a range of approaches that assess the sensitivity of inferences to alternative, routinely non-verifiable assumptions about the missing data process. The final part discusses special topics, such as missing data in clinical trials and sample surveys as well as approaches to model diagnostics in the missing data setting. In each part, an introduction provides useful background material and an overview to set the stage for subsequent chapters. Covering both established and emerging methodologies for missing data, this book sets the scene for future research. It provides the framework for readers to delve into research and practical applications of missing data methods.

Download or read book Meta Analysis with R written by Guido Schwarzer and published by Springer. This book was released on 2015-10-08 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Doing Meta Analysis with R written by Mathias Harrer and published by CRC Press. This book was released on 2021-09-15 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Meta Analysis for Explanation written by Thomas D. Cook and published by Russell Sage Foundation. This book was released on 1992-04-27 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Meta Analysis for Public Management and Policy written by Evan Ringquist and published by John Wiley & Sons. This book was released on 2013-01-03 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for Meta-Analysis for Public Management and Policy "In his usual rigorous but readable style, Evan Ringquist and co-author Mary Anderson have produced a tour-de-force on the topic of meta-analysis in public policy and management research. Meta-analysis is badly needed in the all-too-common situation when researchers have low confidence in summarizing the overall results of dozens of studies on the effectiveness of some policy. This book has a nice combination of conceptual overview, methodological details, and applications that will make it possible for researchers to conduct their own meta-analysis. It is tempting to require all graduate students to write a meta-analysis as a chapter in their dissertation, or include meta-analysis as a standard offering in the research methods curriculum of social science graduate programs. The more people that adopt Ringquist and Anderson's approach, the less resources will be wasted on conducting studies that do not contribute to cumulative scientific knowledge. " —Mark Lubell Department of Environmental Science and Policy Director, Center for Environmental Policy and Behavior University of California-Davis “Ringquist and his colleagues deliver value and add to canon of public management methods by delivering an analytical framework that makes the case for systematic research using the tools of meta-analysis. This book will be a must read for all committed to strengthening evidence-based research that improves public policy and management decision making.” —David M. Van Slyke The Maxwell School of Citizenship and Public Affairs Syracuse University “In Meta-Analysis for Public Management and Policy Evan Ringquist and his colleagues provide a lucid and practical roadmap for policy and public management scholars who use meta-analysis in their research. But this is more than a “how to” volume; it provides background on why meta-analysis is a potent means for accumulating and synthesizing empirical research findings, and shows how its use has evolved in recent decades. Specific applications of meta-analysis to long-standing policy and management debates are given, essentially providing an array of developed “templates” through which scholars and practitioners can assess how to approach different kinds of analytical problems using meta-analysis. Particularly valuable to me is the careful development and presentation of the necessary stages of meta-analysis, from conceptualization through data coding and bias assessment to advanced modeling. All of the statistical analyses can be conducted in Stata, utilizing readily available “.ado” modules. I will use this book, both in research and in the classroom. Overall it is one of the most useful methodological contributions I’ve seen in some time.” —Hank Jenkins-Smith Department of Political Science Director, Center for Applied Social Research University of Oklahoma “Meta-Analysis for Public Management and Policy conveys the considerable untapped potential of meta-analysis to strengthen and advance bodies of knowledge and evidence in public management and policy. This book takes students and researchers deep into the methods of meta-analysis and details of their empirical application, without losing sight of the important policy questions and the implications of choices that researchers make in their empirical work for the production of evidence for public managers and policymakers. This book will serve as an excellent practical guide for those conducting their first meta-analysis, while at the same time supporting critically-focused consumption of existing meta-analyses and discussion of where the field can gainfully take this approach to enhance our research and knowledge bases. It draws in a range of valuable and important examples of applications of meta-analysis techniques throughout the book and rounds off with four full-fledged applications of the method. Although the book reaches out to an audience of public management and policy researchers and consumers of this research, it should be of interest to a broad range of applied social science researchers and students as well.” —Carolyn Heinrich Sid Richardson Professor of Public Affairs Director, Center for Health and Social Policy LBJ School of Public Affairs University of Texas – Austin “Even for incredibly specialized techniques, public management and policy scholars have a multiplicity of methods texts from which to choose. Yet it is truly surprising that a strong guide to applied meta-analysis — a rigorous framework for the organization of empirical findings — has not been available. Ringquist and Anderson provided just that with an accessible guide to sophisticated techniques. Marrying an instructive text to a set of exemplary standalone studies, Meta-Analysis for Public Management and Policy offers unparalleled guidance for instructors and students and more than a little wisdom for seasoned scholars. It is destined to become the standard reference for our field.” —Anthony Michael Bertelli CC Crawford Chair in Management and Performance USC Price School of Public Policy USC Gould School of Law University of Southern California “This comprehensive treatment of meta-analysis is an excellent guide for scholars and students in public management and public policy. The carefully done exposition demonstrates why meta-analysis should have greater use in the profession.” —Kenneth J. Meier Charles H. Gregory Chair in Liberal Arts Department of Political Science Texas A&M University “This remarkable book reviews the history of the use of meta-analysis in the social sciences, argues forcefully for its importance, value, and relevance for public managers, and provides one-stop-shopping for those who want to learn how to do it or understand how others have done it. The detailed coverage of each step in the process allows a student to learn the technique completely while fully understanding the logic and intellectual goals of the enterprise. Most importantly, the authors review techniques from a range of disciplines, drawing most of their positive suggestions from the field of medical statistics rather than the social sciences. The examples and applications, on the other hand, stem from the world of government and public policy. Four chapters provide new syntheses of research on individual policies using the techniques and practices introduced in the earlier chapters. The result is original research, a strong argument for the value of meta-analysis in a field (political science and public administration) that uses it little, and a complete tool-kit for those who would want to apply these powerful ideas on their own. A very impressive and useful text.” —Frank R. Baumgartner Richard J. Richardson Distinguished Professor Department of Political Science University of North Carolina at Chapel Hill “Meta-analysis is a valuable tool for accumulating knowledge about how management matters from across a range of policy areas and disciplines. It is also an underused tool, in large part because of the lack of a comprehensive and useable guide on the topic. Ringquist remedies this problem by offering clear instruction on how to apply the technique wisely, as well as highly useful empirical demonstrations. The field of public management needs this excellent book.” —Donald Moynihan Professor of Public Affairs University of Wisconsin-Madison “Professors and students frequently face decisions about how deeply to invest in a statistical procedure, a new technology, a new theory, or some other development in their discipline. The authors of Meta-Analysis for Public Management and Policy support such a decision about meta-analysis by making a convincing case for its value and increasing utilization, including such steps as a careful consideration of criticisms of the method. Evan Ringquist then provides clearly, engagingly written chapters on the major concepts, procedures, and issues in the techniques of meta-analysis. His coauthors then provide effectively-presented examples of meta-analytic studies about such topics as school voucher effectiveness, public service motivation and performance, and public sector performance management. The accessible and reader-friendly explanations, coupled with the illustrative examples that walk the reader through how to do it, make this a distinctively effective methodological text. In so doing, it offers a distinctively valuable resource for those of us who want to learn more about this important statistical method.” —Hal Rainey Alumni Foundation Distinguished Professor Department of Public Administration and Policy University of Georgia “James Heckman’s Nobel lecture described the combined influence of micro surveys, advances in computers and software, and the development and dissemination of multivariate statistical methods on applied economic research. His comments apply equally well to empirical research throughout the social sciences. These forces have created a “flood of numbers” and advances in technology since he wrote about them have assured that the process is accelerating. We need to transform the ways we learn from empirical analyses and create a science for the analysis of the secondary data from applied statistical and econometric models. This science would include methods for summarizing what has been learned from estimates and tests. It would provide methods for diagnostic screening of results to gauge the importance of modeling assumptions and the types of primary data for the findings being reported. Finally, it may well lead to the development of meta-models—integrating findings intended to describe a single system but viewed thru distinctive empirical lenses. Meta-analysis is a method that takes an important step in developing this science. It is a collection of methods that is a product of the transformation in applied research in the past half century. Initially much of this research was the domain of social scientists working on the evaluation of educational interventions. In these applications the primary data from different studies were routinely available, but the outcome and control variables differed across studies. As a result, the focus for these meta-analyses was on data combination with multiple, distinctive measures for asset of latent variables associated with the hypothesized underlying process. The texts describing meta-analysis focused on these situations. As applications of meta-analysis expanded to economics, political science, and sociology, the data structures changed. The new data came from empirical models –as estimated parameters or summaries of test results. The challenges posed in developing these types of data and understanding what they reveal were distinctly different. A text developed by scholars who appreciate how these types of summaries are different was missing until Ringquist and Anderson’s Meta Analysis for Public Management and Policy. Explaining a process that blends the best of qualitative and quantitative research is a challenge. This book has met this challenge and delivered researchers a great platform for teaching these methods to their students and for updating their own skills. At least four features distinguish this book: 1. The authors display a clear understanding of the strengths and the weaknesses of meta- analysis. Their treatment describes how care in data construction, variable coding, relevant statistical methods and, especially, careful attention to interpreting the findings from a meta-analysis can reinforce the strengths and mitigate the weaknesses. 2. There are real examples presented throughout the book along with a genuine understanding of the importance of the details in developing meta-analyses. 3. The coverage of relevant statistical methods is comprehensive and clear. And 4. The Appendices offer the detail researchers need to see in order to genuinely learn how to use meta analytic methods. It should be in the library of every serious teacher or practitioner”—V. Kerry Smith Regents Professor and W.P. Carey Professor Department of Economics Arizona State University “There are several texts for meta-analysis available, most notably “The Handbook of Research Synthesis and Meta-Analysis” by Cooper, Hedges and Valentine, but none specifically directed to public administration and policy scholars. In fact the points of emphasis and examples make the existing texts both difficult and poorly suited for the applied social sciences. Ringquist’s book is a spectacular success in filling this lacuna. Ringquist provides a clearer encapsulation of “the basics” in its opening section, and the “basics” are tailored to “problem-oriented” policy sciences (noting for instance, that meta-analyses in public management and policy will almost always use random-effects over fixed-effects). The empirical examples woven throughout as well as the actual analyses on PSM and school vouchers are exceptionally useful in identifying the stages of the process. At the same time, the book doesn’t spare the gritty details of confronting commonly required procedures, like bootstrapping and dealing with clustered robust SE, hierarchical modeling, etc. For readers with no exposure to meta-analysis, the text eases the transition by offering a refresher on how statistical techniques are used in original research, then how they differ when used in meta-analysis. Ringquist offers guidelines for syntheses, formulating problems, data evaluation, turning studies into data, techniques in meta-analysis, “the language of meta-analysis”, coding strategies and publication bias. The author also notes that the context and even techniques of meta-analysis are different for public management and public policy compared with medicine and psychology, and education. Public administration and policy analysis provide great opportunities for meta-analysis, but these fields also present considerable challenge. Great care is needed in synthesizing differently designed studies, which are observational and quasi-experimental or correlational designs, because the statistics of meta-analysis were originally developed to synthesize results from experiment design. Measurement issues are tricky because authentic scales are used less frequently than in psychology or medical research. In addition PA and policy as fields of scholarship are diverse and eclectic in research design which makes comparison of parameter estimates exceedingly difficult. Ringquist adroitly compiles an approach to meta-analysis adapted to reflect this context. While Section 1 consists of seven chapters, which discusses techniques of meta-analysis, Section 2 including Chapters 8, 9, 10 and 11 illustrates actual studies using meta-analysis conducted in public management and policy research: evaluating the effectiveness of educational vouchers, performance management in public sector, the effects of federal poverty deconcentration efforts on economic self-sufficiency and problematic behaviors, and the relationship between public service motivation and performance. The book is an easier read than other texts in it guides from project inception through lit review and analysis in a manner tailored to policy and management, and it actually provides a much more accessible and thorough coverage of many of the basic building blocks, random effects, r-based effect sizes, and bootstrapping, making it far more indispensable for any PA meta-analysis. The check-lists for coding articles are especially useful. Provision of Stata commands and practical data management suggestions (creating a command file for data set transformations, for instance) is a great advantage for this text. Adding an addendum with R programming options, in the next edition might be helpful too. The conclusion both compelling and concise but I would like to have seen some of the arguments presented here at the beginning of the book, reserving the conclusion for a fuller encapsulation of what the overall strategy of the book accomplishes in stages – rebutting criticisms that meta-analysis in social science is a waste of time because study estimates are non-comparable and effect sizes non-independent with careful examination of research design and models. This book is essential reading for any scholar in public administration and policy considering undertaking meta-analysis. I expect it will gain many readers in other social science disciplines as well. For serious users of meta-analysis Ringquist’s book will not be the only one on the shelf, but it is a valuable addition.” —Richard Feiock Augustus B. Turnbull Professor Askew School of Public Administration and Policy Florida State University

Download or read book The Handbook of Research Synthesis and Meta Analysis written by Harris Cooper and published by Russell Sage Foundation. This book was released on 2019-06-14 with total page 567 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Individual Participant Data Meta Analysis written by Richard D. Riley and published by John Wiley & Sons. This book was released on 2021-06-08 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Applied Mixed Model Analysis written by Jos W. R. Twisk and published by Cambridge University Press. This book was released on 2019-04-18 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emphasizing interpretation of results, this hands-on guide explains why, when, and how to use mixed models with your data.

Download or read book The Prevention and Treatment of Missing Data in Clinical Trials written by National Research Council and published by National Academies Press. This book was released on 2010-12-21 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: Randomized clinical trials are the primary tool for evaluating new medical interventions. Randomization provides for a fair comparison between treatment and control groups, balancing out, on average, distributions of known and unknown factors among the participants. Unfortunately, these studies often lack a substantial percentage of data. This missing data reduces the benefit provided by the randomization and introduces potential biases in the comparison of the treatment groups. Missing data can arise for a variety of reasons, including the inability or unwillingness of participants to meet appointments for evaluation. And in some studies, some or all of data collection ceases when participants discontinue study treatment. Existing guidelines for the design and conduct of clinical trials, and the analysis of the resulting data, provide only limited advice on how to handle missing data. Thus, approaches to the analysis of data with an appreciable amount of missing values tend to be ad hoc and variable. The Prevention and Treatment of Missing Data in Clinical Trials concludes that a more principled approach to design and analysis in the presence of missing data is both needed and possible. Such an approach needs to focus on two critical elements: (1) careful design and conduct to limit the amount and impact of missing data and (2) analysis that makes full use of information on all randomized participants and is based on careful attention to the assumptions about the nature of the missing data underlying estimates of treatment effects. In addition to the highest priority recommendations, the book offers more detailed recommendations on the conduct of clinical trials and techniques for analysis of trial data.

Download or read book Estimating Treatment Effect in the Presence of Noncompliance Measured with Error written by Leslie Anne Kenna and published by . This book was released on 2001 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Introduction to Meta Analysis written by Michael Borenstein and published by John Wiley & Sons. This book was released on 2011-08-24 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Missing Data in Clinical Studies written by Geert Molenberghs and published by John Wiley & Sons. This book was released on 2007-04-04 with total page 526 pages. Available in PDF, EPUB and Kindle. Book excerpt: Missing Data in Clinical Studies provides a comprehensive account of the problems arising when data from clinical and related studies are incomplete, and presents the reader with approaches to effectively address them. The text provides a critique of conventional and simple methods before moving on to discuss more advanced approaches. The authors focus on practical and modeling concepts, providing an extensive set of case studies to illustrate the problems described. Provides a practical guide to the analysis of clinical trials and related studies with missing data. Examines the problems caused by missing data, enabling a complete understanding of how to overcome them. Presents conventional, simple methods to tackle these problems, before addressing more advanced approaches, including sensitivity analysis, and the MAR missingness mechanism. Illustrated throughout with real-life case studies and worked examples from clinical trials. Details the use and implementation of the necessary statistical software, primarily SAS. Missing Data in Clinical Studies has been developed through a series of courses and lectures. Its practical approach will appeal to applied statisticians and biomedical researchers, in particular those in the biopharmaceutical industry, medical and public health organisations. Graduate students of biostatistics will also find much of benefit.