Multiple linear regression as an analytical tool in cephalometric studies.

Abstract

When the effect is studied of a factor like 'orthodontic therapy' on linear craniofacial growth, the concomitant consequence of age and gender on size cannot be ignored. The methodologically correct solution is division of the study group into smaller units, each of which is homogeneous with respect to age, gender, and therapy, and to compare these with matched controls. Yet, apart from matched controls being hard to find, this method of subdivision has the serious drawback that smaller groups decrease statistical power. A solution without the need to create sub-groups lies in the application of multiple linear regression analysis. It has been applied to biological data in other studies, but verification of the outcome has not been reported so far. Indeed, testing the mathematical assumptions underlying the regression model created unresolvable obstacles and, therefore, it was decided to perform verification by means of practical examples. Two separate tests for the applicability of the multiple linear regression method, on different data, with differing predictor sets, and with different control samples have been performed.