Effect-Size Measures and Meta-Analytic Thinking in Counseling Psychology Research

The Counseling Psychologist

Volumn 34, Issue 5, 2006, Pages 601-629

  Henson, Robin K ^a  

^a UNIVERSITY OF NORTH TEXAS   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 33747081621     PISSN: 00110000     EISSN: None     Source Type: Journal    
DOI: 10.1177/0011000005283558     Document Type: Article

References (82)

1. Aaron, B., Kromrey, J. D., & Ferron, J. (1998, November). Equating “r”-based and “d”-based effect size indices: Problems with a commonly recommended formula. Paper presented at the annual meeting of the Florida Educational Research Association, Orlando. (ERIC Document Reproduction No. ED 433 353)
2. American Psychological Association. (1994). Publication manual of the American Psychological Association (4th ed.). Washington, DC: Author.
3. American Psychological Association. (2001). Publication manual of the American Psychological Association (5th ed.). Washington, DC: Author.
4. Anderson, D. R., Burnham, K. P., & Thompson, W. L. (2000). Null hypothesis testing: Problems, prevalence, and an alternative. Journal of Wildlife Management, 64, 912-923.
5. Bagozzi, R. P., Fornell, C., & Larcker, D. F. (1981). Canonical correlation analysis as a special case of a structural relations model. Multivariate Behavioral Research, 16, 437-454.
6. Bird, K. D. (2002). Confidence intervals for effect sizes in analysis of variance. Educational and Psychological Measurement, 62, 197-226.
7. Campbell, T. C. (2005). An introduction to clinical significance: An alternative index of intervention effect for group experimental designs. Journal of Early Intervention, 27, 210-227.
8. Carver, R. P. (1978). The case against statistical significance testing. Harvard Educational Review, 48, 378-399.
9. Cohen, J. (1968). Multiple regression as a general data-analytic system. Psychological Bulletin, 70, 426-443.
10. Cohen, J. (1969). Statistical power analysis for the behavioral sciences. New York: Academic Press.
11. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.
12. Cohen, J. (1994). The earth is round (p <. 05). American Psychologist, 49, 997-1003.
13. Cohen, J., & Cohen, P. (1983). Applied multiple regression/correlation analysis for the behavioral sciences. Hillsdale, NJ: Lawrence Erlbaum.
14. Courville, T., & Thompson, B. (2001). Use of structure coefficients in published multiple regression articles: β is not enough. Educational and Psychological Measurement, 61, 229-248.
15. 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.
16. Cumming, G., & Finch, S. (2005). Inference by eye: Confidence intervals and how to read pictures of data. American Psychologist, 60, 170-180.
17. Ezekiel, M. (1930). Methods of correlational analysis. New York: John Wiley.
18. Fern, E. F., & Monroe, K. B. (1996). Effect-size estimates: Issues and problems. Journal of Consumer Research, 23, 89-105.
19. Gaston, L., & Marmar, C. R. (1994). The California Psychotherapy Alliance Scale. In A. O. Horvath & L. S. Greenberg (Eds.), The working alliance: Theory, research and practice (pp. 85-108). New York: John Wiley.
20. Glass, G. V. (1976). Primary, secondary, and meta-analysis of research. Educational Researcher, 5(10), 3-8.
21. Harlow, L. L., Mulaik, S. A., & Steiger, J. H. (Eds.). (1997). What if there were no significance tests? Mahwah, NJ: Lawrence Erlbaum.
22. Harris, M. J. (1991). Significance tests are not enough: The role of effect-size estimation in theory corroboration. Theory & Psychology, 1, 375-382.
23. Hays, W. L. (1981). Statistics (3rd ed.). New York: Holt, Rinehart & Winston.
24. Helms, J. E., Henze, K. T., Sass, T. L., & Mifsud, V. A. (2006). Treating Cronbach’s alpha reliability as data in counseling research. The Counseling Psychologist, 34, 630-660.
25. Henson, R. K. (2000). Demystifying parametric analyses: Illustrating canonical correlation as the multivariate general linear model. Multiple Linear Regression Viewpoints, 26, 11-19.
26. Henson, R. K. (2002, April). The logic and interpretation of structure coefficients in multivariate general linear model analyses. Paper presented at the annual meeting of the American Educational Research Association, New Orleans, LA. (ERIC Document Reproduction Service No. ED 467 381)
27. Henson, R. K. (2005, February). From Cohen’s d to Mahalanobis distance: What do they have in common as effect size measures? Paper presented at the annual meeting of the Southwest Educational Research Association, New Orleans, LA.
28. Henson, R. K., Capraro, R. M., & Capraro, M. M. (2004). Reporting practices and use of exploratory factor analyses in educational research journals: Errors and explanation. Research in the Schools, 11, 61-72.
29. Henson, R. K., & Roberts, J. K. (2006). Use of exploratory factor analysis in published research: Common errors and some comment on improved practice. Educational and Psychological Measurement, 66, 393-416.
30. Henson, R. K., & Smith, A. D. (2000). State of the art in statistical significance and effect size reporting: A review of the APA Task Force report and current trends. Journal of Research and Development in Education, 33, 285-296.
31. Hinkle, D. E., Wiersma, W., & Jurs, S. G. (2003). Applied statistics for the behavioral sciences (5th ed.). Boston: Houghton Mifflin.
32. Horvath, A. O., & Greenberg, L. (1989). Development and validation of the Working Alliance Inventory. Journal of Counseling Psychology, 36, 223-233.
33. Hoyt, W. T., Warbasse, R. E., & Chu, E. Y. (in press [TCP special issue, part 2]). Construct validation in counseling psychology research. The Counseling Psychologist, 34.
34. 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.
35. Huberty, C. J. (1993). Historical origins of statistical testing practices: The treatment of Fisher versus Neyman-Pearson views in textbooks. Journal of Experimental Education, 61, 317-333.
36. Huberty, C. J. (2002). A history of effect size indices. Educational and Psychological Measurement, 62, 227-240.
37. Huberty, C. J., & Lowman, L. L. (2000). Group overlap as a basis for effect size. Educational and Psychological Measurement, 60, 543-563.
38. 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. 1-22). Stamford, CT: JAI.
39. Jacobson, N. S., Follette, W. C., & Revenstorf, D. (1984). Psychotherapy outcome research: Methods for reporting variability and evaluating clinical significance. Behavior Therapy, 15, 336-352.
40. Jacobson, N. S., Roberts, L. J., Berns, S. B., & McGlinchey, J. B. (1999). Methods for defining and determining the clinical significance of treatment effects: Description, application, and alternatives. Journal of Consulting and Clinical Psychology, 67, 300-307.
41. Jacobson, N. S., & Truax, P. (1991). Clinical significance: A statistical approach to defining meaningful change in psychotherapy research. Journal of Consulting and Clinical Psychology, 59, 12-19.
42. Kahn, J. H. (2006). Factor analysis in counseling psychology research, training, and practice: Principles, advances, and applications. The Counseling Psychologist, 34, 684-718.
43. Kazdin, A. E. (1977). Assessing the clinical or applied importance of behavior change through social validation. Behavior Modification, 1, 427-452.
44. Kazdin, A. E. (1999). The meanings and measurement of clinical significance. Journal of Consulting and Clinical Psychology, 67, 332-339.
45. Kendall, P. C., & Grove, W. M. (1988). Normative comparisons in therapy outcome. Behavioral Assessment, 10, 147-158.
46. Kendall, P. C., Marrs-Garcia, A., Nath, S. R., & Sheldrick, R. C. (1999). Normative comparisons for the evaluation of clinical significance. Journal of Consulting and Clinical Psychology, 67, 285-299.
47. Keselman, H.J., Huberty, C.J., Lix, L.M., Olejnik, S., Cribbie, R.A., Donahue, B., et al. (1998). Statistical practices of educational researchers: An analysis of their ANOVA, MANOVA, and ANCOVA analyses. Review of Educational Research, 68, 350-386.
48. Kirk, R. E. (1996). Practical significance: A concept whose time has come. Educational and Psychological Measurement, 56, 746-759.
49. Kline, R. B. (2004). Beyond significance testing: Reforming data analysis methods in behavioral research. Washington, DC: American Psychological Association.
50. Knapp, T. R. (1978). Canonical correlation analysis: A general parametric significance testing system. Psychological Bulletin, 85, 410-416.
51. Leach, L. F., & Henson, R. K. (2003, February). The use and impact of adjusted R2 effects in published regression research. Paper presented at the annual meeting of the Southwest Educational Research Assocation, San Antonio, TX.
52. Martens, M. P., & Hasse, R. F. (in press [TCP special issue, part 2]). Advanced applications of structural equation modeling in counseling psychology research. The Counseling Psychologist, 34.
53. Maxwell, S. E., & Delaney, H. D. (1990). Designing experiments and analyzing data. Belmont, CA: Wadsworth.
54. McLean, J. E., & Ernest, J. M. (1998). The role of statistical significance testing in educational research. Research in the Schools, 5, 15-22.
55. Nelson, N., Rosenthal, R., & Rosnow, R. L. (1986). Interpretation of significance levels and effect sizes by psychological researchers. American Psychologist, 41, 1299-1301.
56. Nietzel, M. T., & Trull, T. J. (1988). Meta-analytic approaches to social comparisons: A method for measuring clinical significance. Behavioral Assessment, 10, 146-159.
57. Olejnik, S., & Algina, J. (2000). Measures of effect size for comparative studies: Applications, interpretations, and limitations. Contemporary Educational Psychology, 25, 241-286.
58. Quintana, S. M., & Minami, T. (in press [TCP special issue, part 2]). Guidelines for meta-analyses of counseling psychology research. The Counseling Psychologist, 34.
59. Roberts, J. K., & Henson, R. K. (2002). Correction for bias in estimating effect sizes. Educational and Psychological Measurement, 62, 241-253.
60. Rosenthal, R., & Gaito, J. (1963). The interpretation of level of significance by psychological researchers. Journal of Psychology, 55, 33-38.
61. Rosnow, R. L., & Rosenthal, R. (1989). Statistical procedures and the justification of knowledge in psychological science. American Psychologist, 44, 1276-1284.
62. Sherry, A. (2006). Discriminant analysis in counseling psychology research. The Counseling Psychologist, 34, 661-683.
63. Sherry, A., & Henson, R. K. (2005). Conducting and interpreting canonical correlation analysis in personality research: A user-friendly primer. Journal of Personality Assessment, 84, 37-48.
64. Smithson, M. (2000). Statistics with confidence. Thousand Oaks, CA: Sage.
65. 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.
66. Snyder, P., & Lawson, S. (1993). Evaluating results using corrected and uncorrected effect size estimates. Journal of Experimental Education, 61, 334-349.
67. Super, D. E. (1949). Appraising vocational fitness. New York: Harper & Row.
68. Thompson, B. (1991). A primer on the logic and use of canonical correlation analysis. Measurement and Evaluation in Counseling and Development, 24, 80-95.
69. Thompson, B. (1994). The concept of statistical significance testing. Measurement Update, 4, 5-6.
70. Thompson, B. (1996). AERA editorial policies regarding statistical significance testing: Three suggested reforms. Educational Researcher, 25, 26-30.
71. Thompson, B. (2001). Significance, effect sizes, stepwise methods, and other issues: Strong arguments move the field. Journal of Experimental Education, 70, 80-93.
72. Thompson, B. (2002). What future quantitative social science research could look like: Confidence intervals for effect sizes. Educational Researcher, 31, 25-32.
73. Tracey, T. J., & Kokotovic, A. M. (1989). Factor structure of the Working Alliance Inventory. Psychological Assessment, 1, 207-210.
74. Trusty, J., Thompson, B., & Petrocelli, J. V. (2004). Practical guide for reporting effect size in quantitative research in the Journal of Counseling & Development. Journal of Counseling & Development, 82, 107-110.
75. Tryon, W. W. (2001). Evaluating statistical difference, equivalence, and indeterminacy using inferential confidence intervals: An integrated alternative methods of conducting null hypothesis significance tests. Psychological Methods, 6, 371-386.
76. Vacha-Haase, T., Nilsson, J. E., Reetz, D. R., Lance, T. S., & Thompson, B. (2000). Reporting practices and APA editorial policies regarding statistical significance and effect size. Theory & Psychology, 10, 413-425.
77. Vacha-Haase, T., & Thompson, B. (2004). How to estimate and interpret various effect sizes. Journal of Counseling Psychology, 51, 473-481.
78. Weston, R., & Gore, P. A., Jr. (2006). A brief guide to structural equation modeling. The Counseling Psychologist, 34, 719-751.
79. Wilkinson, L., & Task Force on Statistical Inference. (1999). Statistical methods in psychology journals: Guidelines and explanation. American Psychologist, 54, 594-604.
80. Worthington, R. L., & Whittaker, T. A. (in press [TCP special issue, part 2]). Scale development research: A content analysis and recommendations for best practices. The Counseling Psychologist, 34.
81. Yin, P., & Fan, X. (2001). Estimating R2 shrinkage in multiple regression: A comparison of analytical methods. Journal of Experimental Education, 69, 203-224.
82. Zuckerman, M., Hodgins, H. S., Zuckerman, A., & Rosenthal, R. (1993). Contemporary issues in the analysis of data: A survey of 551 psychologists. Psychological Science, 4, 49-53.