Using Partial Residual Plots in Assessing and Improving the Construct Validity of Multiple Regression Models

Abstract

Advantages of partial residual plots over residual plots in regression analysis are discussed and illustrated by empirical examples. A variation of partial residual equation is introduced and an effective procedure to use this revised form in identifying the proper transformation for achieving linearity and variance stabilization is presented. Essentially, the transformed predictors are identified by partial residual plots and introduced into the regression model to improve the regression fit. Uses, limitations and strengths of partial residual plots are discussed.