Partial Correlation Coefficient Comparison in Graphical Gaussian Models
Alberto Roverato · COMPSTAT · 1996
In graphical Gaussian models the partial correlation coefficient is the natural measure of the interaction represented by an edge of the independence graph. In this paper we discuss the comparison of partial correlation coefficients in a graphical Gaussian model. Three tests of the null hypothesis H 0: ρ12.3 = ρ13.2 in a trivariate Normal distribution with ρ23.1 = 0 are worked out. The methods include the likelihood ratio test and the restricted maximum likelihood estimates are provided in closed form. A sampling simulation study for comparing the three test statistics is carried out.