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The Reviewer's Guide to Quantitative Methods in the Social Sciences
Abstract
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.
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“Each TAQ item was checked to see if it was normally distributed. According to the guideline, if the skewness was ≤2.0 and the kurtosis was ≤7.0, the item can be regarded as a normal distribution [25].”
From Validation of the Tinnitus Acceptance Questionnaire: Japanese Version (2022) · cites this paper as [25]
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“The normality test indicated that the main variables met the assumption of normal distribution (kurtosis < |7.0|, skew-ness < |2.0|; Hancock & Mueller, 2010).”
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“The skewness and kurtosis of CU behaviors, conduct problem, and surgency fell within the acceptable range (i.e., skewness < |2.0| and kurtosis < |7.0|; Hancock and Mueller, 2010).”
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Descriptive Statistics for the 236 Extracted Variables
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Models for Professional Learning: An Imperative for Enhancing Teacher Leadership
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Pattern Coefficients for the 236 Features
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“Major textbooks on general and specific methods (e.g., Bollen, 1989; Field, 2005; Fitzmaurice et al., 2004; Goldstein, 2011; Hancock and Mueller, 2010; Little and Rubin, 2002; Tabachnik and Fidell, 2007) make complex methodologies accessible to junior researchers and for experienced researchers who…”
MethodKocalar, H. E. (2024) · Thesis Commons (OSF Preprints) · doi:10.31237/osf.io/7eymh
Metadata
- Authors
- Hancock, G. R., Mueller, R. O., Stapleton, L. M., & Mueller, R. O.
- Venue
- Routledge eBooks
- Publisher
- Routledge
- Published
- 2010-04-26
- OpenAlex
- W4214816511
- Cited by
- 942
- References
- 0
- Citations by year
- 2026: 20 · 2025: 56 · 2024: 68 · 2023: 74 · 2022: 75 · 2021: 71 · 2020: 70 · 2019: 96 · 2018: 74 · 2017: 74 · 2016: 86 · 2015: 57 · 2014: 44 · 2013: 39 · 2012: 18
- FWCI
- 28.10
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Routledge eBooks (publishedVersion)
- Topics
- Social Sciences › Education › Diverse Academic Research Areas
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychology Research and Bibliometrics
- Keywords
- quantitative methods, peer review, manuscript review, research proposals, statistical analysis, methodological assumptions, methodological limitations, research design, social sciences, behavioral science
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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