I've used a general linear model function to run an ANCOVA, involving a categorical predictor (with two levels), a continuous predictor, and their interaction effect.
If I don't center the continuous predictor, I get a significant effect for the categorical predictor and a significant interaction effect. If I mean-center the covariate, the categorical predictor effect becomes non-significant but the other effects remain unaltered. Does anyone know why this happens? And which option is the correct one (to center or not to center?)?