--- Barth Riley <[email protected]> wrote:
> I am conducting a CHAID model to examine potential interaction of
> several categorical variables in explaining variance in a dependent
> variable. CHAID models do not have the capability of forcing
> covariates into the model, i.e., examining the effect of the
> predictors on the dependent after controlling for the effect of the
> covariate(s). To get around this limitation, I want to perform a
> regression analysis of the same dependent variable with the covariate
> as the sole predictor, then use the dependent variable partialling
> out the effect of the covariate (call it y prime) as the target
> variable in the CHAID model. Would y prime be the value predicted
> by the regression model?
I have no idea what a CHAID model is and -findit chaid- does not show
anything up either. However, the dependent variable after you have
partialed out the effect of your covariate is not the predicted value,
but the residual. The predicted value is the part of y that can be
explained by your covariate. The residual is the part of y that cannot
be explained by your covariate.
Hope this helps,
Maarten
-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting address:
Buitenveldertselaan 3 (Metropolitan), room Z434
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
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