Parametric Alternatives to the Analysis of Variance

The ANOVA, Welch, and Brown and Forsyth tests for mean equality were compared using Monte Carlo methods. The tests’ rates of Type I error and power were examined when populations were non-normal, variances were heterogeneous, and group sizes were unequal. The ANOVA F test was most affected by the as...

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Bibliographic Details
Published in:Journal of educational and behavioral statistics 1982-09, Vol.7 (3), p.207-214
Main Authors: Clinch, Jennifer J., Keselman, H. J.
Format: Article
Language:English
Subjects:
Variance analysis
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Summary:The ANOVA, Welch, and Brown and Forsyth tests for mean equality were compared using Monte Carlo methods. The tests’ rates of Type I error and power were examined when populations were non-normal, variances were heterogeneous, and group sizes were unequal. The ANOVA F test was most affected by the assumption violations. The test proposed by Brown and Forsyth appeared, on the average, to be the “best” test statistic for testing an omnibus hypothesis of mean equality.
ISSN:1076-9986
0362-9791
1935-1054
DOI:10.3102/10769986007003207