Effect Sizes for Research: Univariate and Multivariate Applications [NOOK Book]

Overview

Noted for its comprehensive coverage and practical approach, this new edition – which features 40% new material – covers the use of univariate and multivariate effect sizes.


Many measures and estimators are reviewed along with their application, interpretation, and limitations. The book features numerous examples using real data for a variety of variables and designs, to help readers apply the material to their own data. Tips on the use of ...

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Effect Sizes for Research: Univariate and Multivariate Applications

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Overview

Noted for its comprehensive coverage and practical approach, this new edition – which features 40% new material – covers the use of univariate and multivariate effect sizes.


Many measures and estimators are reviewed along with their application, interpretation, and limitations. The book features numerous examples using real data for a variety of variables and designs, to help readers apply the material to their own data. Tips on the use of SPSS, SAS, R, and S-Plus are provided.


Intended as a resource for professionals, researchers, and advanced students in a variety of fields, this book is also an excellent supplement for advanced statistics courses in psychology, education, the social sciences, business, and medicine.

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Product Details

  • ISBN-13: 9781135611460
  • Publisher: Taylor & Francis
  • Publication date: 4/29/2014
  • Sold by: Barnes & Noble
  • Format: eBook
  • Pages: 272
  • Sales rank: 1,108,707
  • File size: 3 MB

Meet the Author

Robert J. Grissom is a Professor Emeritus and Adjunct Professor of Psychology at San Francisco State University and a Consultant in Statistics. He received his Ph.D. in Psychology from Princeton University. Co-founder of the Graduate Program in Psychological Research at San Francisco State, Dr. Grissom has written numerous chapters and articles on effect size methodology.

John J. Kim is a Professor of Psychology at San Francisco State University. He received his Ph.D. from the Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology in 1993. The current Associate Vice President for Academic Resources at San Francisco State, Dr. Kim has written numerous chapters and articles on effect size methodology.

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Table of Contents

1. Introduction. 2. Confidence Intervals for Comparing the Averages of Two Groups. 3. The Standardized Difference Between Means. 4. Correlational Effect Sizes and Related Topics. 5. Parametric and Nonparametric Effect Size Measures that Go Beyond Comparing Two Averages. 6. Effect Sizes for One-Way ANOVA and Nonparametric Approaches. 7. Effect Sizes for Factorial Designs. 8. Effect Sizes for Categorical Variables. 9. Effect Sizes for Ordinal Categorical Dependent Variables (Rating Scales). 10. Effect Sizes for Multiple Regression/Correlation. 11. Effect Sizes for Analysis of Covariance. 12. Effect Sizes for Multivariate Analysis of Variance.

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