Noted for its comprehensive coverage, this greatly expanded new
edition now covers the use of univariate and multivariate effect
sizes. Many measures and estimators are reviewed along with their
application, interpretation, and limitations. Noted for its
practical approach, 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. The book's broad disciplinary appeal
results from its inclusion of a variety of examples from
psychology, medicine, education, and other social sciences. Special
attention is paid to confidence intervals, the statistical
assumptions of the methods, and robust estimators of effect sizes.
The extensive reference section is appreciated by all.
With more than 40% new material, highlights of the new editon
include:
- three new multivariate chapters covering effect sizes for
analysis of covariance, multiple regression/correlation, and
multivariate analysis of variance
- more learning tools in each chapter including introductions,
summaries, "Tips and Pitfalls" and more conceptual and
computational questions
- more coverage of univariate effect sizes, confidence intervals,
and effect sizes for repeated measures to reflect their increased
use in research
- more software references for calculating effect sizes and their
confidence intervals including SPSS, SAS, R, and S-Plus
- the data used in the book are now provided on the web along
with new data and suggested calculations with IBM SPSS syntax for
computational practice.
Effect Sizes for Research covers standardized and unstandardized
differences between means, correlational measures, strength of
association, and parametric and nonparametric measures for between-
and within-groups data.
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. A
prerequisite of introductory statistics through factorial analysis
of variance and chi-square is recommended.
General
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!