Burke Johnson wrote:
>
> 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?
Your predictions will be the same regardless of the coding of the dummy
variables. The parameter estimates (and thus the associated t-tests or
F-tests) may change depending on the coding, but the parameter estimates
are not unique anyway when categorical variables are used.
--
Paige Miller
Eastman Kodak Company
[EMAIL PROTECTED]
"It's nothing until I call it!" -- Bill Klem, NL Umpire
