A regression Paradox for linear models: sufficient conditions and geometric interpretation
01 January 2009
An analysis of customer survey data using direct and reverse regression leads to apparently inconsistent conclusions. The phenomenon is known as the regression paradox. We describe sufficient conditions when the regression paradox will appear both analytically and geometrically. In linear models, it is a result of a distribution shift among groups relative to predictability in regression and reverse regression.