Evaluating the Effect of Incorrect Specification of a Regression Model

Abstract

This is the second part of a two-part paper on the effect of incorrectly specifying a regression model. The first five sections of the paper appeared in the last issue of this journal. These sections dealt with statistical models, model underspecification and overspecification, and bias and root mean square error. A new computer program, EXPLOR II, which permits evaluation of the consequences of model misspecification, was briefly described. Finally, the concepts were illustrated with an example involving a rubber tear-strength test program. In this part of the paper, the concepts are applied to evaluating the alias structure of fractional factorial test plans. Various effects of model underspecification are described and some concluding remarks are made. The formulae that are used to evaluate bias are given in the Appendix.

• Bias Evaluation
• Experimental Design
• Misspecified Model

Additional information

Notes on contributors

Gerald J. Hahn

Dr. Hahn is Manager, Statistics Program, Corporate Research and Development, General Electric Company. He is a fellow of ASQC.

Paul I. Feder

Dr. Feder is an associate professor in the Statistics Department of the Ohio State University. He is a former employee of General Electric Corporate Research and Development. He is a member of ASQC.

William Q. Meeker

Dr. Meeker is an assistant professor in the Statistics Department of the Iowa State University. He was formerly associated with the Industrial Administration Institute of Union College and General Electric Corporate Research and Development.