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Parametric Alternatives to the Analysis of Variance

Author

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  • Jennifer J. Clinch
  • H. J. Keselman

Abstract

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.

Suggested Citation

  • Jennifer J. Clinch & H. J. Keselman, 1982. "Parametric Alternatives to the Analysis of Variance," Journal of Educational and Behavioral Statistics, , vol. 7(3), pages 207-214, September.
    • Handle: RePEc:sae:jedbes:v:7:y:1982:i:3:p:207-214
    DOI: 10.3102/10769986007003207
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    Cited by:

    1. Zhou Xiao-Hua & Wanzhu Tu, 1999. "Comparison of Several Independent Population Means When Their Samples Contain Log-Normal and Possibly Zero Observations," Biometrics, The International Biometric Society, vol. 55(2), pages 645-651, June.

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