Regression diagnostic using an orthogonalized variables based stepwise regression procedure

Regression diagnostic for identifying the causes that limit the precision and/or stability of a regression model is considered. The diagnostic procedure uses the indicators generated in the SROV process that was proposed recently by Shacham and Brauner (1998b). These indicators consider the signal-to-noise ratio in the independent and dependent variables data. It is shown that a routine used of the SROV procedure for regression of experimental data enables identification of the optimal model when the precision of the model is limited only by the accuracy of the experimental data. Otherwise, the indicators generated by the SROV procedure and the guidelines given in the paper can help to pinpoint the potential causes, so that remedial actions can be taken.