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Biometrika 1976 63(1):214-215; doi:10.1093/biomet/63.1.214
© 1976 by Biometrika Trust
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Miscellanea

On testing equality of related correlation coefficients

DOUGLAS A. WOLFE

Department of Statistics, Ohio State University

Let (X1, X2, X3) have a trivariate distribution with mean vector µ and covariance matrix {Sigma} having (i, j)th element {sigma}ij={rho}ij{sigma}i{sigma}j with {rho}ij= 1(i, j=1, 2, 3). If we are interested in testing the hypothesis H:{rho}12={rho}13 against appropriate alternatives under a variety of assumptions about the form of the trivariate distribution, but with no further restrictions on {Sigma}, we could use one of the many asymptotic or conditional procedures that are available; see, for example, Aitkin, Nelson & Reinfurt (1968), Corsten (1970) and Dunn & Clark (1969). On the other hand, an exact, small-sample, unconditional test of H does not appear to be tractable for this general {Sigma}. We show that by placing a mild restriction on {Sigma}, such a small-sample test of H can be based on a simple, single product-moment correlation coefficient between the variables X1 and X3X2 provided that the conditional distribution of X1 given X3X2, is normal.

Key Words: Covariance matrices • Equality of regressions • Exact tests • Related correlation coefficients


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