Abstract
Canonical variate analysis often involves the construction of confidence regions round points representing group means in a 2-dimensional plot. Traditionally circles have always been constructed, but some authors have recently advocated ellipses as being more appropriate. This paper describes a Monte Carlo study investigating the effect of a range of factors on the inclusion rates of true population means within both types of region for normal data. The traditional circles do not perform too badly within a restricted range, but they are nearly always under-included. The ellipses usually have higher inclusion rates, and so are often closer to the nominal rate, but are sometimes over-included.
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References
Campbell, N. A. (1984) Canonical variate analysis—a general model formulation.Australian Journal of Statistics,26, 86–96.
Heiberger, R. M. (1978) Generation of random orthogonal matrices.Applied Statistics,27, 199–206.
Krzanowski, W. J. (1988)Principles of Multivariate Analysis: a User's Perspective, Clarendon Press, Oxford.
Krzanowski, W. J. (1989) On confidence regions in canonical variate analysis.Biometrika,76, 107–116.
Lubishew, A. A. (1962) On the use of discriminant functions in taxonomy.Biometrics,18, 455–477.
Schott, J. R. (1990) Canonical mean projections and confidence regions in canonical variate analysis.Biometrika,77, 587–596.
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Ringrose, T.J., Krzanowski, W.J. Simulation study of confidence regions for canonical variate analysis. Stat Comput 1, 41–46 (1991). https://doi.org/10.1007/BF01890835
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DOI: https://doi.org/10.1007/BF01890835