Effect sizes, confidence intervals, and confidence intervals for effect sizes

Psychology in the Schools

Volumn 44, Issue 5, 2007, Pages 423-432

  Thompson, Bruce ^a  

^a TEXAS A AND M UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 34250900995     PISSN: 00333085     EISSN: 15206807     Source Type: Journal    
DOI: 10.1002/pits.20234     Document Type: Article

References (58)

1. Algina, J., & Keselman, H.J. (2003). Approximate confidence intervals for effect sizes. Educational and Psychological Measurement, 63, 537-553.
2. Algina, J., Keselman, H.J., & Penfield, R.D. (2005a). An alternative to Cohen's standardized mean difference effect size: A robust parameter and confidence interval in the two independent groups case. Psychological Methods, 10, 317-328.
3. Algina, J., Keselman, H.J., & Penfield, R.D. (2005b). Effect sizes and their intervals: The two-level repeated measures case. Educational and Psychological Measurement, 65, 241-258.
4. American Psychological Association. (2001). Publication manual of the American Psychological Association (5th ed.). Washington, DC: Author.
5. Andersen, D.R., Burnham, K.P., & Thompson, W.L. (2000). Null hypothesis testing: Problems, prevalence, and an alternative. Journal of Wildlife Management, 64, 912-923.
6. Berkson, J. (1938). Some difficulties of interpretation encountered in the application of the Chisquare test. Journal of the American Statistical Association, 33, 526-536.
7. Boring, E.G. (1919). Mathematical vs. scientific significance. Psychological Bulletin, 16, 335-338.
8. Capraro, R.M., & Capraro, M.M. (2002). Treatments of effect sizes and statistical significance tests in textbooks. Educational and Psychological Measurement, 62, 771-782.
9. Carver, R. (1978). The case against statistical significance testing. Harvard Educational Review, 48, 378-399.
10. Cohen, J. (1968). Multiple regression as a general data-analytic system. Psychological Bulletin, 70, 426-443.
11. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.
12. Cohen, J. (1994). The earth is round (p < .05). American Psychologist, 49, 997-1003.
13. Cumming, G., & Finch, S. (2001). A primer on the understanding, use, and calculation of confidence intervals that are based on central and noncentral distributions. Educational and Psychological Measurement, 61, 532-574.
14. Cumming, G., & Finch, S. (2005). Inference by eye: Confidence intervals and how to read pictures of data. American Psychologist, 60, 170-180.
15. Fidler, F. (2002). The fifth edition of the APA Publication Manual: Why its statistics recommendations are so controversial. Educational and Psychological Measurement, 62, 749-770.
16. Finch, S., Cumming, G., & Thomason, N. (2001). Reporting of statistical inference in the Journal of Applied Psychology: Little evidence of reform. Educational and Psychological Measurement, 61, 181-210.
17. Greenwald, A.G. (1975). Consequences of prejudice against the null hypothesis. Psychological Bulletin, 82, 1-20.
18. Grissom, R.J. (1994). Probability of the superior outcome of one treatment over another. Journal of Applied Psychology, 79, 314-316.
19. Grissom, R.J., & Kim, J.J. (2005). Effect sizes for research: A broad practical approach. Mahwah, NJ: Erlbaum.
20. Hays, W.L. (1981). Statistics (3rd ed.). New York, NY: Holt, Rinehart and Winston.
21. Hedges, L. V. ( 1981 ). Distribution theory for Glass's estimator of effect size and related estimators. Journal of Educational Statistics, 6, 107-128.
22. Hedges, L.V. (1982). Estimation of effect size from a series of independent experiments. Psychological Bulletin, 92, 490-499.
23. Hess, B., Olejnik, S., & Huberty, C.J. (2001). The efficacy of two improvement-over-chance effect sizes for two-group univariate comparisons under variance heterogeneity and nonnormality. Educational and Psychological Measurement, 61, 909-936.
24. Hubbard, R., & Ryan, P.A. (2000). The historical growth of statistical significance testing in psychology-And its future prospects. Educational and Psychological Measurement, 60, 661-681.
25. Huberty, C.J. (2002). A history of effect size indices. Educational and Psychological Measurement, 62, 227-240.
26. Huberty, C.J., & Holmes, S.E. (1983). Two-group comparisons and univariate classification. Educational and Psychological Measurement, 43, 15-26.
27. Huberty, C.J., & Pike, C.J. (1999). On some history regarding statistical testing. In B. Thompson (Ed.), Advances in social science methodology (Vol. 5, pp. 1-23). Stamford, CT: JAI Press.
28. Johnson, D.H. (1999). The insignificance of statistical significance testing. Journal of Wildlife Management, 63, 763-772.
29. Keselman, H.J., Algina, J., & Fradette, K. (in press). Robust confidence intervals for effect size in the two-group case. Journal of Modem Applied Statistical Methods.
30. Kieffer, K.M., Reese, R.J., & Thompson, B. (2001). Statistical techniques employed in AERJ and JCP articles from 1988 to 1997: A methodological review. Journal of Experimental Education, 69, 280-309.
31. Kirk, R.E. (1996). Practical significance: A concept whose time has come. Educational and Psychological Measurement, 56, 746-759.
32. Kirk, R.E. (2003). The importance of effect magnitude. In S.F. Davis (Ed.), Handbook of research methods in experimental psychology (pp. 83-105). Oxford, UK: Blackwell.
33. Kline, R.B. (2004). Beyond significance testing: Reforming data analysis methods in behavioral research. Washington, DC: American Psychological Association.
34. Knapp, T.R. (1978). Canonical correlation analysis: A general parametric significance-testing system. Psychological Bulletin, 85, 410-416.
35. Natesan, P., & Thompson, B. (2007). Extending improvement-over-chance I-index effect size simulation studies to cover some small-sample cases. Educational and Psychological Measurement, 67, 59-72.
36. 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.
37. Prentice, D.A., & Miller, D.T. (1992). When small effects are impressive. Psychological Bulletin, 112, 160-164.
38. Rosenthal, R. (1979). The file drawer problem and tolerance for null results. Psychological Bulletin, 86, 638-641.
39. Rosenthal, R. (1994). Parametric measures of effect size. In H. Cooper & L.V. Hedges (Eds.), The handbook of research synthesis (pp. 231-244). New York: Russell Sage Foundation.
40. Rosnow, R.L., & Rosenthal, R. (1989). Statistical procedures and the justification of knowledge in psychological science. American Psychologist, 44, 1276-1284.
41. Rozeboom, W.W. (1997). Good science is abductive, not hypothetico-deductive. In L.L. Harlow, S.A. Mulaik, & J.H. Steiger (Eds.), What if there were no significance tests? (pp. 335-392). Mahwah, NJ: Erlbaum.
42. Schmidt, F.L. (1996). Statistical significance testing and cumulative knowledge in psychology: Implications for training of researchers. Psychological Methods, 1, 115-129.
43. Schmidt, F.L., & Hunter, J.E. (1997). Eight common but false objections to the discontinuation of significance testing in the analysis of research data. In L.L. Harlow, S.A. Mulaik, & J.H. Steiger (Eds.), What if there were no significance tests? (pp. 37-64). Mahwah, NJ: Erlbaum.
44. 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.
45. Steiger, J.H., & Fouladi, R.T. (1992). R2: A computer program for interval estimation, power calculation, and hypothesis testing for the squared multiple correlation. Behavior Research Methods, Instruments, and Computers, 4, 581-582.
46. Suter, G.W., II. (1996). Abuse of hypothesis testing statistics in ecological risk assessment. Human Ecological Risk Assessment, 2, 331-347.
47. Thompson, B. (1996). AERA editorial policies regarding statistical significance testing: Three suggested reforms. Educational Researcher, 25, 26-30.
48. Thompson, B. (2001). Significance, effect sizes, stepwise methods, and other issues: Strong arguments move the field. Journal of Experimental Education, 70, 80-93.
49. Thompson, B. (2002a). "Statistical," "practical," and "clinical": How many kinds of significance do counselors need to consider? Journal of Counseling and Development, 80, 64-71.
50. Thompson, B. (2002b). What future quantitative social science research could look like: Confidence intervals for effect sizes. Educational Researcher, 31, 24-31.
51. Thompson, B. (2004). The "significance" crisis in psychology and education. Journal of Socio-Economies, 33, 607-613.
52. Thompson, B. (2006a). Foundations of behavioral statistics: An insight-based approach. New York: Guilford.
53. Thompson, B. (2006b). Research synthesis: Effect sizes. In J.L. Green, G. Camilli, & P.B. Elmore (Eds.), Handbook of complementary methods in education research (pp. 583-603). Mahwah, NJ: Erlbaum.
54. Vacha-Haase, T., & Thompson, B. (2004). How to estimate and interpret various effect sizes. Journal of Counseling Psychology, 51, 473-481.
55. 2 biased, and if so, what is the best correction formula? Journal of Experimental Education, 75, 109-125.
56. Wilkinson, L., & Task Force on Statistical Inference, American Psychological Association, Science Directorate. (1999). Statistical methods in psychology journals: Guidelines and explanations. American Psychologist, 54, 594-604.
57. Yoccuz, N.G. (1991). Commentary: Use, overuse, and misuse of significance tests in evolutionary biology and ecology. Bulletin of the Ecology Society of America, 72, 106-111.
58. Ziliak, S.T., & McCloskey, D.N. (2004). Size matters: The standard error of regressions in the American Economic Review. Journal of Socio-Economies, 33, 527-546.