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Robust techniques for testing heterogeneity of variance effects in factorial designs

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Abstract

Several ways of using the traditional analysis of variance to test heterogeneity of spread in factorial designs with equal or unequaln are compared using both theoretical and Monte Carlo results. Two types of spread variables, (1) the jackknife pseudovalues ofs 2 and (2) the absolute deviations from the cell median, are shown to be robust and relatively powerful. These variables seem to be generally superior to the Z-variance and Box-Scheffé procedures.

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References

  • Appelbaum, M. I., & Cramer, E. M. Some problems in the nonorthogonal analysis of variance.Psychological Bulletin, 1974,81, 335–347.

    Google Scholar 

  • Basu, J. P., Odell, P. L., & Lewis, T. O. The effects of intraclass correlation on certain significance tests when sampling from multivariate normal population.Communications in Statistics, 1974,3, 899–908.

    Google Scholar 

  • Box, G. E. P., & Andersen, S. L. Permutation theory in the derivation of robust criteria and the study of departures from assumption.Journal of the Royal Statistical Society, Series B, 1955,17, 1–26.

    Google Scholar 

  • Brown, M. B., & Forsythe, A. B. Robust tests for equality of variances.Journal of the American Statistical Association, 1974,69, 364–367.

    Google Scholar 

  • Games, P. A., Winkler, H. R., & Probert, D. A. Robust tests for homogeneity of variance.Educational and Psychological Measurement, 1972,32, 887–909.

    Google Scholar 

  • Gartside, P. S. A study of methods for comparing several variances.Journal of the American Statistical Association, 1972,67, 342–346.

    Google Scholar 

  • Glass, G. V., Peckham, P. D., & Sanders, J. R. Consequences of failure to meet assumptions underlying the fixed effects analyses of variance and covariance.Review of Educational Research, 1972,42, 237–288.

    Google Scholar 

  • Gray, H. L., & Schucany, W. R.The generalized jackknife statistic. New York: Marcel Dekker, 1972.

    Google Scholar 

  • Hays, W. L.Statistics for the social sciences (2nd ed.). New York: Holt, Rinehart, & Winston, 1973.

    Google Scholar 

  • Kendall, M. G., & Stuart, A.The advanced theory of statistics (Vol. 1, 3rd ed.). London: Charles Griffin, 1969.

    Google Scholar 

  • Layard, M. W. J. Robust large sample tests for homogeneity of variances.Journal of the American Statistical Association, 1973,68, 195–198.

    Google Scholar 

  • Levene, H. Robust tests for the equality of variances. In I. Olkin, S. G. Ghurye, W. Hoeffding, W. G. Madow, & H. B. Mann (Eds.),Contributions to probability and statistics Palo Alto: Stanford University Press, 1960.

    Google Scholar 

  • Levy, K. J. An empirical comparison of theZ-variance and Box-Scheffé tests for homogeneity of variance.Psychometrika, 1975,40, 519–524.

    Google Scholar 

  • Marsaglia, G., & Bray, T. A. One-line random number generators and their use in combinations.Communications of the ACM, 1968,11, 757–759.

    Google Scholar 

  • Martin, C. G. Comment on Levy's “An empirical comparison of theZ-variance and Box-Scheffé tests for homogeneity of variance.”Psychometrika, 1976,41, 551–556.

    Google Scholar 

  • Miller, R. G., Jr. Jackknifing variances.Annals of Mathematical Statistics, 1968,39, 567–582.

    Google Scholar 

  • Miller, R. G., Jr. The jackknife—a review.Biometrika, 1974,61, 1–15.

    Google Scholar 

  • Mosteller, F., & Tukey, J. W. Data analysis, including statistics. In G. Lindzey & E. Aronson (Eds.),The handbook of social psychology (Vol. 2, 2nd ed.). Reading, Mass.: Addison-Wesley, 1968.

    Google Scholar 

  • O'Brien, R. G. Factorial designs for the analysis of spread. (Doctoral dissertation, University of North Carolina, 1975).Dissertation Abstracts International, 1976,37, 1328B. (University Microfilms No. 76-20,062)

  • Overall, J. E., & Woodward, J. A. A simple test for heterogeneity of variance in complex factorial designs.Psychometrika, 1974,39, 311–318.

    Google Scholar 

  • Scheffé, H. A.The analysis of variance. New York: Wiley, 1959.

    Google Scholar 

  • Zelen, M. Factorial experiments in life testing.Technometrics, 1959,1, 269–288.

    Google Scholar 

  • Zelen, M. Analysis of two-factor classifications with respect to life tests. In I. Olkin, S. G. Ghurye, W. Hoeffding, W. G. Madow, & H. B. Mann (Eds.),Contributions to probability and statistics. Palo Alto: Stanford University Press, 1960.

    Google Scholar 

  • Walsh, J. E. Concerning the effect of intraclass correlation on certain significant tests.Annals of Mathematical Statistics, 1947,18, 88–96.

    Google Scholar 

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This research was sponsored by Public Health Service Training Grant MH-08258 from the National Institute of Mental Health. The author thanks Mark I. Appelbaum, Elliot M. Cramer, and Scott E. Maxwell for their helpful criticisms of this paper. An earlier version of this work was presented at the Annual Meeting of the Psychometric Society, Murray Hill, New Jersey, April, 1976.

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O'Brien, R.G. Robust techniques for testing heterogeneity of variance effects in factorial designs. Psychometrika 43, 327–342 (1978). https://doi.org/10.1007/BF02293643

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  • DOI: https://doi.org/10.1007/BF02293643

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