Meta Analysis In Social Research

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 The author shows how to identify questions that can be answered using meta-analysis, retrieve both published and unpublished studies, create a coding manual, use traditional and unique effect size indices, and write a meta-analytic review.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

Praised in the first edition for the clarity of his general framework for conceptualizing meta-analysis, Rosenthal's revised edition covers the latest techniques in the field, such as a new effect size indicator for one size data, a new coefficient of robustness of replication, new procedures for combining and comparing effect sizes for multiple dependent variables, and new data on the magnitude of the problem of incomplete retrieval (the file drawer problem).

How is a social scientist to cope with the cornucopia of already existing studies in his or her area? How to draw useable conclusions from a body of work that might run to 5000 items? Traditional narrative integration fails to usefully portray such accumulated knowledge. Meta-analysis is an approach that systematically analyzes and synthesizes research. This book is its first full explanation. Meta-analysis treats a field of research as a complex set of data to be accumulated and integrated. As such it has much in common with survey research -- though, as causal relationships may have already been established by the studies being surveyed meta-analysis need not suffer from the limitations of survey research as a tool for establishing causes. Besides showing how to derive generalizations from very large and divergent bodies of research, the authors also provide ways for enhancing the findings of few or small research studies, and techniques for evaluating the findings of individual experiments by contrasting them with the combined weight of findings from other studies. Their approach does not enforce uniformity on different research. I

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

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.

"This book offers readers the best of both worlds: technical sophistication coupled with user-friendly, practical information for doing meta-analysis." -- Page 4 of cover.

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

Scientific progress often begins with the difficult task of preparing informed, conclusive reviews of existing research. Since the 1970s, the traditional "subjective" approach to research reviewing in the social sciences has been challenged by a statistical alternative known as meta-analysis. Meta-analysis provides a principled method of distilling reliable generalizations from previous studies on a single topic, thereby providing a quantitative and objective background for future research. The Future of Meta-Analysis brings together expert researchers for an in-depth examination of this new methodology—not to promote a consensus view but rather to explore from several perspectives the theories, tensions, and concerns of meta-analysis, and to illustrate through concrete examples the rationale behind meta-analytic decisions. In a meta-analysis prepared especially for this volume, a statistician and a psychologist review the existing literature on aphasia treatment. In a second study, experts analyze six still-unpublished meta-analyses sponsored by the National Institute of Education to investigate the effects of school desegregation on the academic achievement of black children. This unique case study approach provides valuable discussion of the process of meta-analysis and of the current implications of meta-analysis for policy assessment. Prepared under the auspices of the National Research Council, The Future of Meta-Analysis presents a forum for leaders in this rapidly evolving field to discuss salient conceptual and technical issues and to offer a new theoretical framework, further methodological guidance, and statistical innovations that anticipate a future in which meta-analysis will play an even more effective and valuable role in social science research.