Predictor centering
= Predictor centering
{title2=$z=x-c$}
Replacing a numerical predictor $x$ by $x-c$ preserves the fitted mean space and slope in a <linear regression> containing an intercept. The intercept becomes the fitted mean at $x=c$. In <simple linear regression>, centering at the sample mean makes intercept and slope estimates uncorrelated under a <normal linear model>. This changes coefficient interpretation, not predictions.