ALTERNATIVE MODELSINVOLVING MULTIPLE VARIABLES FOR PARTIAL CORRELATION ANALYSES AND THEIR APPLICATIONS.

Title of Publication: ALTERNATIVE MODELSINVOLVING MULTIPLE VARIABLES FOR PARTIAL CORRELATION ANALYSES AND THEIR APPLICATIONS.
Author(s): Usoro Anthony E., Omekara C. O
Year of Publication: 2012
ABSTRACT
This paper aims at providing various ways of alternating variables so that the number of variables held constant produces the same number of alternative models whose computations give the same result for a particular partial correlation coefficient. Significantly, the numerical verification carried out to show the validity of the alternative models has shown that, in a multiple variable case, there is no one way solution to obtaining a partial correlation coefficient, when the floating effects of others are under control. Hence, we have shown the number of variables held constant in partial correlation gives exact number of alternative ways of providing a result for particular partial correlation coefficient.

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