Hi,
A student of mine is getting ready to develop a GLM prediction model that will include
a mixture of categorical and quantitative predictor variables. We will probably not
include interaction terms in the model (i.e., it will be a main effects only model).
Here's my question: Do you suggest using dummy coding (0,1) or effects coding (1,0,-1)
for the categorical variables included in the model?
The reason I'm asking is because dummy coding does not always give the same result for
a factorial design as does ANOVA and effects coding, and, hence, Pedhazur recommends
using effects coding rather than dummy coding in the factorial case. Do you know if
the choice of dummy or effects coding matters for a main effects only model with
multiple categorical and quantitatively scaled predictor variables?
Thanks in advance,
Burke Johnson
