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On testing equality of related correlation coefficients
Department of Statistics, Ohio State University
Let (X1, X2, X3) have a trivariate distribution with mean vector µ and covariance matrix
having (i, j)th element
ij=
ij
i
j with
ij= 1(i, j=1, 2, 3). If we are interested in testing the hypothesis H:
12=
13 against appropriate alternatives under a variety of assumptions about the form of the trivariate distribution, but with no further restrictions on
, 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
. We show that by placing a mild restriction on
, 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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