Regression analysis is widely used to estimate the effects of relative policy proximity on relative candidate evaluations. Using the 1984 NES data, we show that the functional form for specifying distance between voter and candidate can lead to different results concerning which policy variables significantly affect relative candidate evaluations. Simple statistics do not allow us to choose the distance specification most consistent with least-squares assumptions. A series of diagnostic tests are offered to make this determination.