I'm analysing my data using linear mixed effects models and I have noticed that the high estimated correlation of fixed effects may be indicating some collinearity problem:
Correlation of Fixed Effects: (Intr) typcmp gpbjct typecomplex -0.588 gapobject -0.588 0.500 typcmplx:gp 0.416 -0.707 -0.707
I've centered the predictors using the following code:
datsub$c.gap = factor(datsub$gap) contrasts(datsub$c.gap) = c(1, -1) datsub$c.type = factor(datsub$type) contrasts(datsub$c.type) = c(1, -1)
I've run my model again, and now the correlation of fixed effects seems to be zero:
Correlation of Fixed Effects: (Intr) c.typ1 c.gap1 c.type1 0.000 c.gap1 0.000 0.000 c.typ1:c.g1 0.000 0.000 0.000
Is this even possible? Am I centering my predictors in the wrong way?