The Reviewer's Guide to Quantitative Methods in the Social Sciences / Edition 1

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Overview

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:

Comprehensive Coverage — Thirty-one chapters cover virtually all of the popular classic and emerging quantitative techniques, thus helping reviewers to evaluate a manuscript's methodological approach and it's data analysis. In addition, the volume serves as an indispensable reference tool for those designing their own research.

Unique Chapter Format — For ease of use, all chapters follow the same structure.

The opening page of each chapter destines 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.

Expert Chapter Authors—Chapters are written by methodological and applied scholars who are expert in the particular quantitative method being reviewed.

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Product Details

  • ISBN-13: 9780415965088
  • Publisher: Taylor & Francis
  • Publication date: 2/11/2010
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 448
  • Sales rank: 867,373
  • Product dimensions: 6.80 (w) x 9.90 (h) x 1.00 (d)

Meet 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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Table of Contents

List of Figures x

List of Tables xi

Preface xiii

Acknowledgements xvi

1 Analysis of Variance: Between-Groups Designs Alan J. Klockars 1

2 Analysis of Variance: Repeated Measures Designs Lisa M. Lix H. J. Keselman 15

3 Canonical Correlation Analysis Xitao Fan Timothy R. Konold 29

4 Cluster Analysis Dena A. Pastor 41

5 Correlation and Other Measures of Association Jason W. Osborne 55

6 Discriminant Analysis Carl J. Huberty 71

7 Effect Sizes and Confidence Intervals Geoff Cumming Fiona Fidler 79

8 Factor Analysis: Exploratory and Confirmatory Deborah L. Bandalos Sara J. Finney 93

9 Generalizability Theory Amy Hendrickson Ping Yin 115

10 Hierarchical Linear Modeling D. Betsy Mccoach 123

11 Interrater Reliability and Agreement William T. Hoyt 141

12 Item Response Theory R. J. De Ayala 155

13 Latent Class Analysis Karen M. Samuelsen C. Mitchell Dayton 173

14 Latent Growth Curve Models Kristopher J. Preacher 185

15 Latent Transition Analysis David Rindskopf 199

16 Latent Variable Mixture Models Gitta Lubke 209

17 Logistic Regression Ann A. O'Connell K. Rivet Amico 221

18 Log-Linear Analysis Ronald C. Serlin Michael A. Seaman 241

19 Meta-Analysis S. Natasha Beretvas 255

20 Multidimensional Scaling Mark L. Davison Cody S. Ding Se-Kang Kim 265

21 Multiple Regression Ken Kelley Scott E. Maxwell 281

22 Multitrait-Multimethod Analysis Keith F. Widaman 299

23 Multivariate Analysis of Variance Stephen Olejnik 315

24 Power Analysis Kevin R. Murphy 329

25 Reliability and Validity of Instruments Thomas R. Knapp Ralph O. Mueller 337

26 Research Design Sharon Anderson Dannels 343

27 Single Subject Design and Analysis Andrew L. Egel Christine H. Barthold 357

28 Structural Equation Modeling Ralph O. Mueller Gregory R. Hancock 371

29 Structural Equation Modeling: Multisample Covariance and Mean Structures Richard G. Lomax 385

30 Survey Sampling, Administration, and Analysis Laura M. Stapleton 397

31 Survival Analysis Paul D. Allison 413

Lift of Contributors 425

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