LINK BETWEEN ORTHOGONAL AND STANDARD MULTIPLE LINEAR-REGRESSION MODELS

Several topics in connection with a recently proposed method for the o rthogonalization of predictor variables (dominant component analysis) are considered. Applying the sequential regression procedure, it is sh own that dominant component analysis and the standard multiple linear regression method are directly related to each other. In addition, it is demonstrated that an earlier proposed iterative procedure for the o rthogonalization of a correlated variable can be efficiently replaced by one step regression. It is also shown that the coefficient of deter mination for an orthogonal descriptor coincides with the corresponding squared semipartial correlation coefficient. Finally, the origin of e xtra information in an orthogonalized predictor variable is discussed.