Testing treatment effects in repeated measures designs: An update for psychophysiological researchers

Psychophysiology

Volumn 35, Issue 4, 1998, Pages 470-478

  Keselman, H J ^a  

^a UNIVERSITY OF MANITOBA   (Canada)

Author keywords

Main, interaction and contrast tests; New analyses; Repeated measurements

Indexed keywords

ARTICLE; COMPARATIVE STUDY; DATA ANALYSIS; MULTIVARIATE ANALYSIS; OUTCOMES RESEARCH; PRIORITY JOURNAL; PSYCHOPHYSIOLOGY; STATISTICAL ANALYSIS; STATISTICAL MODEL; STUDY; TREATMENT OUTCOME;

EID: 0031747780     PISSN: 00485772     EISSN: None     Source Type: Journal    
DOI: 10.1017/S0048577298000237     Document Type: Article

References (74)

1. Akaike, H. (1974). Anew look at the statistical model identification. IEEE Transaction on Automatic Control, AC-19, 716-723.
2. Algina, J. (1994). Some alternative approximate tests for a split plot design. Multivariate Behavioral Research, 29, 365-384.
3. Algina, J. (1997). Generalization of improved general approximation tests to split plot designs with multiple between-subjects factors and/or multiple within-subjects factors. British Journal of Mathematical and Statistical Psychology, 50, 243-252.
4. Algina, J., & Keselman, H. J. (1997). Detecting repeated measures effects with univariate and multivariate statistics. Psychological Methods, 2, 208-218.
5. Algina, J., & Keselman, H. J. (in press). A power comparison of the Welch-James and Improved General Approximation tests in the split-plot design. Journal of Educational and Behavioral Statistics.
6. Bartlett, M. S. (1939). A note on tests of significance in multivariate analysis. Proceedings of the Cambridge Philosophical Society, 35, 180-185.
7. Best, D. J., & Rayner, J. C. W. (1987). Welch's approximate solution for the Behrens-Fisher problem. Technometrics, 29, 205-210.
8. Betz, M. A., & Gabriel, K. R. (1978). Type IV errors and analysis of simple effects. Journal of Educational Statistics, 3, 121-143.
9. Boik, R. J. (1993). The analysis of two-factor interactions in fixed effects linear models. Journal of Educational Statistics, 18, 1-40.
10. Box, G. E. P. (1954). Some theorems on quadratic forms applied in the study of analysis of variance problems: I. Effects of inequality of variance in the one-way classification. Annals of Mathematical Statistics, 25, 290-302.
11. BMDP Statistical Software Inc. (1994). BMDP new system for Windows (Version 1) [computer software]. Los Angeles: Author.
12. Collier, R. O., Jr., Baker, F. B., Mandeville, G. K., & Hayes, T. F. (1967). Estimates of test size for several test procedures based on conventional variance ratios in the repeated measures design. Psychometrika, 32, 339-353.
13. Davidson, M. L. (1972). Univariate versus multivariate tests in repeated measures experiments. Psychological Bulletin, 77, 446-452.
14. Fisher, R. A. (1935). The design of experiments. London: Oliver & Boyd.
15. Games, P. A., & Howell, J. F. (1976). Pairwise multiple comparison procedures with unequal N's and/or variances: A Monte Carlo study. Journal of Educational Statistics, 1, 113-125.
16. Greenhouse, S. W., & Geisser, S. (1959). On methods in the analysis of profile data. Psychometrika, 24, 95-112.
17. Hayter, A. J. (1986). The maximum familywise error rate of Fisher's least significant difference test. Journal of the American Statistical Association, 81, 1000-1004.
18. Hochberg, Y. (1988). A sharper Bonferroni procedure for multiple tests of significance. Biometrika, 75, 800-802.
19. Hochberg, Y., & Tamhane, A. C. (1987). Multiple comparison procedures. New York: John Wiley.
20. Hotelling, H. (1931). The generalization of Student's ratio. Annals of Mathematical Statistics, 2, 360-378.
21. Hotelling, H. (1951). A Generalized t test and measure of multivariate dispersion. In J. Neyman (Ed.), Proceedings of the Second Berkeley Symposium on Mathematical Statistics and Probability. Berkeley: University of California Press.
22. Huynh, H. (1978). Some approximate tests for repeated measurement designs. Psychometrika, 43, 161-175.
23. Huynh, H. S., & Feldt, L. (1970). Conditions under which mean square ratios in repeated measurements designs have exact F distributions. Journal of the American Statistical Association, 65, 1582-1589.
24. Huynh, H., & Feldt, L. S. (1976). Estimation of the Box correction for degrees of freedom from sample data in randomized block and split-plot designs. Journal of Educational Statistics, 1, 69-82.
25. James, G. S. (1951). The comparison of several groups of observations when the ratios of the population variances are unknown. Biometrika, 38, 324-329.
26. James, G. S. (1954). Tests of linear hypotheses in univariate and multivariate analysis when the ratios of the population variances are unknown. Biometrika, 41, 19-43.
27. Jennings, J. R. (1987). Editorial policy on analyses of variance with repeated measures. Psychophysiology, 24, 474-475.
28. Johansen, S. (1980). The Welch-James approximation to the distribution of the residual sum of squares in a weighted linear regression. Biometrika, 67, 85-92.
29. Keselman, H. J. (1993). Stepwise multiple comparisons of repeated measures means under violations of multisample sphericity. In F. M. Hoppe (Ed.), Multiple comparisons, selection, and applications in biometry (pp. 167-186). New York: Dekker.
30. Keselman, H. J. (1994). Stepwise and simultaneous multiple comparison procedures of repeated measures' means. Journal of Educational Statistics, 19, 127-162.
31. Keselman, H. J. & Algina, J. (1996). The analysis of higher-order repeated measures designs. In B. Thompson (Ed.), Advances in social science methodology (Vol. 4) (pp. 45-70). Greenwich, CT: JAI Press.
32. Keselman, H. J., Algina, J., Kowalchuk, R. K., & Wolfinger, R. D. (1997). A comparison of recent approaches to the analysis of repeated measurements. Unpublished manuscript.
33. Keselman, H. J., Algina, J., Kowalchuk, R. K., & Wolfinger, R. D. (in press). A comparison of too approaches for selecting covariance structures in the analysis of repeated measurements.
34. Keselman, H. J., Carriere, K. C., & Lix, L. M. (1993). Testing repeated measures hypotheses when covariance matrices are heterogeneous. Journal of Educational Statistics, 18, 305-319.
35. Keselman, H. J., & Keselman, J. C. (1988). Repeated measures multiple comparison procedures: Effects of violating multisample sphericity in unbalanced designs. Journal of Educational Statistics, 13, 215-226.
36. Keselman, H. J., & Keselman, J. C. (1993). Analysis of repeated measurements. In L. K. Edwards (Ed.), Applied analysis of variance in behavioral science (pp. 105-145). New York: Dekker.
37. Keselman, H. J., Keselman, J. C., & Lix, L. M. (1995). The analysis of repeated measurements: Univariate tests, multivariate tests, or both? British Journal of Mathematical and Statistical Psychology, 48, 319-338.
38. Keselman, H. J., Keselman, J. C., & Shaffer, J. P. (1991). Multiple pairwise comparisons of repeated measures means under violation of multisample sphericity. Psychological Bulletin, 110, 162-170.
39. Keselman, H. J., & Rogan, J. C. (1980). Repeated measures F tests and psychophysiological research: Controlling the number of false positives. Psychophysiology, 17, 499-503.
40. Keselman, J. C., & Keselman, H. J. (1990). Analysing unbalanced repeated measures designs. British Journal of Mathematical and Statistical Psychology, 43, 265-282.
41. Kirk, R. E. (1995). Experimental design: Procedures for the behavioral sciences (3rd ed.). New York: Brooks/Cole.
42. Kogan, L. S. (1948). Analysis of variance: Repeated measurements. Psychological Bulletin, 45, 131-143.
43. Lawley, D. N. (1938). A generalization of Fisher's z test. Biometrika, 30, 180-187, 467-469.
44. Lecoutre, B. (1991). A correction for the ε̃ approximate test in repeated measures designs with two or more independent groups. Journal of Educational Statistics, 16, 371-372.
45. Lix, L. M., & Keselman, H. J. (1995). Approximate degrees of freedom tests: A unified perspective on testing for mean equality. Psychological Bulletin, 117, 547-560.
46. Lix, L. M., & Keselman, H. J. (1996). Interaction contrasts in repeated measures designs. British Journal of Mathematical and Statistical Psychology, 49, 147-162.
47. Maxwell, S. E. (1980). Pairwise multiple comparisons in repeated measures designs. Journal of Educational Statistics, 5, 269-287.
48. Maxwell, S. E., & Delaney, H. D. (1990). Designing experiments and analyzing data: A model comparison perspective. Belmont, CA: Wadsworth.
49. Mendoza, J. L. (1980). A significance test for multisample sphericity. Psychometnka, 45, 495-498.
50. Muller, K. E., & Barton, C. N. (1989). Approximate power for repeated measures ANOVA lacking sphericity. Journal of the American Statistical Association, 84, 549-555.
51. Muller, K. E., & Barton, C.N. (1991). Correction to "Approximate power for repeated measures ANOVA lacking sphericity." Journal of the American Statistical Association, 86, 255-256.
52. Norusis, M. J. (1993). SPSS for Windows, advanced statistics (Release 6.0) [computer software], Chicago: SPSS.
53. O'Brien, R. G., & Muller, K. E. (1993). Unified power analysis for t-tests through multivariate hypotheses. In L. K Edwards (Ed.), Applied analysis of variance in behavioral science (pp. 297-344). New York: Dekker.
54. Olson, C. L. (1974). Comparative robustness of six tests in multivariate analysis of variance. Journal of the American Statistical Association, 69, 894-908.
55. Overall, J. E., & Doyle, S. R. (1994). Estimating sample sizes for repeated measurement designs. Controlled Clinical Trials, 15, 100-123.
56. Pillai, K. C. S. (1955). Some new test criteria in multivariate analysis. Annals of Mathematical Statistics, 26, 117-121.
57. Rogan, J. C., Keselman, H. J., & Mendoza, J. L. (1979). Analysis of repeated measurements. British Journal of Mathematical and Statistical Psychology, 32, 269-286.
58. Rouanet, H., & Lepine, D. (1970). Comparison between treatments in a repeated measures design: ANOVA and multivariate methods. British Journal of Mathematical and Statistical Psychology, 23, 147-163.
59. Roy, S. N. (1953). On a heuristic method of test construction and its use in multivariate analysis. Annals of Mathematical Statistics, 24, 220-238.
60. SAS Institute. (1989). SAS/IML software: Usage and reference (Version 6). Cary, NC: Author.
61. SAS Institute. (1990). SAS/STAT user's guide: Volume 2, GLM-VARCOMP (Version 6). Cary, NC: Author.
62. SAS Institute. (1996). SAS/STAT software: Changes and enhancements through release 6.11. Cary, NC: Author.
63. Satterthwaite, F. E. (1941). Synthesis of variance. Psychometrika, 6, 309-316.
64. Satterthwaite, F. E. (1946). An approximate distribution of estimates of variance components. Biometrics, 2, 110-114.
65. Schwarz, G. (1978). Estimating the dimension of a model. Annals of Statistics, 6, 461-464.
66. Seaman, M. A., Levin, J. R., & Serlin, R. C. (1991). New developments in pairwise multiple comparisons: Some powerful and practical procedures. Psychological Bulletin, 110, 577-586.
67. Shaffer, J. P. (1979). Comparison of means: An F test followed by a modified multiple range procedure. Journal of Educational Statistics, 4, 14-23.
68. Shaffer, J. P. (1986). Modified sequentially rejective multiple test procedures. Journal of the American Statistical Association, 81, 826-831.
69. Toothaker, L. E. (1991). Multiple comparisons for researchers. Newbury Park, CA: Sage.
70. Vassey, M. W., & Thayer, J. F. (1987). The continuing problem of false positives in repeated measures ANOVA in psychophysiology: A multivariate solution. Psychophysiology, 24, 479-486.
71. Welch, B. L. (1938). The significance of the difference between two means when the population variances are unequal. Biometrika, 29, 350-362.
72. Welch, B. L. (1947). The generalization of Student's problem when several different population variances are involved. Biometrika, 34, 28-35.
73. Welch, B. L. (1951). On the comparison of several mean values: An alternative approach. Biometrika, 38, 330-336.
74. Wilks, S. S. (1932). Certain generalizations in the analysis of variance. Biometrika, 24, 471-494.