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The Reviewer’s Guide to Quantitative Methods in the Social Sciences

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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.

448 pages, Paperback

First published February 11, 2010

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Profile Image for Veronica.
12 reviews3 followers
May 7, 2020
definitely a good one to keep in your library. I reference it from time to time to think about the quality of my analysis and manuscript. I would say to meet every single criterion is a tall order but good to set a high standard to ensure you don't go down a slippery slope of poor quality research.
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