The First Word: A Letter From the Co-Editors: Effect Sizes—An Explanation of JAA Editorial Policy

Journal of Advanced Academics

Volumn 20, Issue 2, 2009, Pages 209-213

  McCoach, D Betsy ^a   Siegle, Del ^a  

^a UNIVERSITY OF CONNECTICUT   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84861998872     PISSN: 1932202X     EISSN: 21629536     Source Type: Journal    
DOI: 10.1177/1932202X0902000201     Document Type: Article

References (10)

1. Bonett D. G., (2008). Confidence intervals for standardized linear contrasts of means. Psychological Method, 13, 99–109
2. Cumming G., Finch S., (2001). A primer of the understanding, use, and calculation of confidence intervals that are based on central and noncentral distributions. Educational and Psychological Measurement, 61, 532–574
3. Grissom R. J., Kim J. J., (2005). Effect sizes for research: A broad practical approach. Mahwah, NJ: Lawrence Erlbaum
4. Keselman H., (1975). A Monte Carlo investigation of three estimates of treatment magnitude: Epsilon squared, eta squared, and omega squared. Canadian Psychological Review, 16, 44–48
5. Levine T. R., Hullett C. R., (2002). Eta squared, partial eta squared, and misreporting of effect size in communication research. Human Communication Research, 28, 612–625
6. Olejnik S., Algina J., (2000). Measures of effect size for comparative studies: Applications, interpretations, and limitations. Contemporary Educational Psychology, 25, 241–286
7. Olejnik S., Algina J., (2003). Generalized eta and omega squared statistics: Measures of effect size for some common research designs. Psychological Methods, 8, 434–447
8. Smithson M., (2001). Correct confidence intervals for various regression effect sizes and parameters: The importance of noncentral distributions in computing intervals. Educational and Psychological Measurement, 61, 605–632
9. Thompson B., (2002). What future quantitative research could look like: Confidence intervals for effect sizes. Educational Researcher, 31, 25–32
10. Wilkinson L., & the Task Force on Statistical Inference. (1999). Statistical methods in psychology journals: Guidelines and explanations. American Psychologist, 54, 594–604