How to keep the Type I Error Rate in ANOVA if Variances are Heteroscedastic

Authors

  • Karl Moder Institute of Applied Statistics and Computing, University of Natural Resources and Applied Life Sciences, Vienna

DOI:

https://doi.org/10.17713/ajs.v36i3.329

Abstract

One essential prerequisite to ANOVA is homogeneity of variances in underlying populations. Violating this assumption may lead to an increased type I error rate. The reason for this undesirable effect is due to the calculation of the corresponding F-value. A slightly different test statistic keeps the level ®. The underlying distribution of this alternative method is Hotelling’s T2. As Hotelling’s T2 can be approximated by a Fisher’s F-distribution, this alternative test is very similar to an ordinary analysis of variance.

References

Abdi, H. (2007). O’brien test for homogeneity of variance. In N. Salkind (Ed.), Encyclopedia of measurement and statistics. Thousand Oaks, CA: Sage.

Algina, J., Olejnik, S., and Ocanto, R. (1989). Type I error rates and power estimates for selected two-sample tests of scale. Annals of Educational Statistics, 14(4), 373-384.

Box, G. (1954a, June). 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(2), 290-302.

Box, G. (1954b, September). Some theorems on quadratic forms applied in the study of analysis of variance problems, II. effect of inequality of variances and of correlation of errors in the two-way classification. Annals of Mathematical Statistics, 25(3), 484-498.

Box, G., and Andersen, L. (1955). Theory in the derivation of robust criteria and the study of departures from assumption. Journal of the Royal Statistical Society (Series B), 17, 1-34.

Conover, W., Johnson, M., and Johnson, M. (1981, November). A comparative study of tests for homogeneity of variances, with applications to the outer continental shelf bidding data. Technometrics, 23(4), 351-361.

Hotelling, H. (1947). Multivariate quality control. In C. Eisenhart, M. W. Hastay, and W. A. Wallis (Eds.), Techniques of statistical analysis. New York: McGraw-Hill.

Levene, H. (1960). Robust tests for the equality of variance. Contributions to Probability and Statistics, 278-292.

Lindman, H. R. (1992). Analysis of variance in experimental design (S. Fienberg and I. Olkin, Eds.). Springer-Verlag New York, Inc.

Nelson, P. R., and Dudewicz, E. J. (2002). Exact analysis of means with unequal variances. Technometrics, 44(2), 152-160.

O’Brien, R. G. (1979). A general anova method for robust tests of additive models for variances. Journal of the American Statistical Association, 74, 877-880.

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Published

2016-04-03

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Articles

How to Cite

How to keep the Type I Error Rate in ANOVA if Variances are Heteroscedastic. (2016). Austrian Journal of Statistics, 36(3), 179–188. https://doi.org/10.17713/ajs.v36i3.329