Advantages of examining multicollinearities in regression analysis.

Abstract

In this paper a regression analysis is performed with data on spinal cord injuries in order to demonstrate the benefits of determining which, if any, multicollinearities are present in prediction data. Existing multicollinearities are shown to be useful both in determining characteristics of the sampled population as well as explaining possible erratic behavior of variable selection procedures. Latent root regression is performed on the data to illustrate one method of using biased regression techniques to incorporate knowledge of multicollinearities in developing prediction equations.

Cite this paper

@article{Gunst1977AdvantagesOE, title={Advantages of examining multicollinearities in regression analysis.}, author={Richard F. Gunst and Robert L. Mason}, journal={Biometrics}, year={1977}, volume={33 1}, pages={249-60} }