Publication: Tests for bivariate symmetry against ordered alternatives in square contingency tables
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Publication Date
2003-03
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Blackwell
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Abstract
Let X and Y denote two ordinal response variables, each having I levels. When subjects are classified on both variables, there are I-2 possible combinations of classifications. Let p(ij) = Pr(X = i, Y = j). This paper introduces a family of tests based on phi-divergence measures for testing H-0: p(ij) = p(ji) against H-1: p(ij) greater than or equal to p(ji) (i greater than or equal to j); and for testing H-1 against H-2: p(ij) unrestricted. A simulation study assesses some of the family of tests introduced in this paper in comparison to the likelihood ratio test.
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Agresti, A. (1990). Categorical Data Analysis. NewYork:Wiley.
Ali, S.M. & Silvey, S.D. (1966).A general class of coefficient of divergence of one distribution from another. J. Roy. Statist. Soc. 286, 131–142.
Andersen, E.B. (1998). Introduction to the Statistical Analysis of Categorical Data. Berlin: Springer.
Barmi, H.E.&Kochar, S.C. (1995). Likelihood ratio tests for bivariate symmetry against ordered alternatives in a squared contingency table. Statist. Probab. Lett. 22, 167–173.
Bishop, M.M., Fienberg, S.E & Holland, P.W. (1975). Discrete Multivariate Analysis:Theory and Practice. Cambridge, Mass: MIT Press.
Bowker, A. (1948). A test for symmetry in contingency tables. J. Amer. Statist. Assoc. 43, 572–574.
Cressie, N. & Read, T.R.C. (1984). Multinomial goodness-of-fit tests. J. Roy. Statist. Soc. Ser. B 46, 440–464.
Csiszár, I. (1963). Eine Informationstheoretische Ungleichung und ihre Anwendung auf den bewis der Ergodizität on Markhoffschen Ketten. Publ. Math. Inst. Hungar. Acad. Sci. 8, 84–108.
Robertson, T., Wright, F.T. & Dykstra, R.L. (1988). Order Restricted Statistical Inference. New York: Wiley.
Sprent, P. (1993). Applied Nonparametric Statistical Methods. London: Chapman & Hall.