The Reviewer’s Guide to Quantitative Methods in the Social Sciences is designed for evaluators of research manuscripts and proposals in the social and behavioral sciences, and beyond. Its thirty-one uniquely structured chapters cover both traditional and emerging methods of quantitative data analysis, which neither junior nor veteran reviewers can be expected to know in detail. The book updates readers on each technique’s key principles, appropriate usage, underlying assumptions, and limitations. It thereby assists reviewers to offer constructive commentary on works they evaluate, and also serves as an indispensable author’s reference for preparing sound research manuscripts and proposals.
Key features include:
The chapters cover virtually all of the popular classic and emerging quantitative techniques, thus helping reviewers to evaluate a manuscript’s methodological approach and its data analysis. In addition, the volume serves as an indispensable reference tool for those designing their own research.
For ease of use, all chapters follow the same structure:
- the opening page of each chapter defines and explains the purpose of that statistical method
- the next one or two pages provide a table listing various criteria that should be considered when evaluating and applying that methodological approach to data analysis
- the remainder of each chapter contains numbered sections corresponding to the numbered criteria listed in the opening table. Each section explains the role and importance of that particular criterion.
Chapters are written by methodological and applied scholars who are expert in the particular quantitative method being reviewed.
DAVID L. STREINER
Baycrest Centre and University of Toronto
Toronto, Ontario, Canada
–Journal of Personality Assessment, 93(1), 105-106, 2011
From the Back Cover
"This is a book that I would want to have. Anyone reading an article and not understanding a method could consult this book. As well, anyone trying to locate the method for their problems would use this book." — Bruce Wampold, University of Wisconsin
About the Author
Gregory R. Hancock is Professor and Chair of the Department of Measurement, Statistics, and Evaluation at the U. of Maryland and is Director of their Center for Integrated Latent Variable Research.
Ralph O. Mueller is Professor and Dean of the College of Education, Nursing and Health Professions at the University of Hartford.
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