On  9-Apr-2004, [EMAIL PROTECTED] (Paul Benson) wrote:

>  [EMAIL PROTECTED]

> Hi.  I just posted a question on h. regression.  Maybe it would
> be useful to provide some specifics of my analysis.  My DV is
> a measure of parent involvement in the education of their disabled
> child.  I actually enter only 3 groups of IVs, not 4.  My DVs were
> grouped and entered in the analyses thusly:
>
> 1.  a measure of family SES;
> 2.  2 measures of child functioning; and
> 3.  2 measures of social support (1 family support, 1 school support).
>
> In equation 1 -- SES is highly significant.
> In equation 2  --SES significance dropped by ns (.156) and the child
> functioning measures are
>         both significant at the .05 level.
> In equation 3 -- SES and the child functioning measures become
> insignificant and the 2 newly
>         measures both are highly significant at the .01 level or better.
>        Overall the
>         r-squared of these models are .06, .15. and .42 so the support
>        measures are
>         really the critical predictors of parent involvement here.

Paul,

I believe that there may be other types of models that will handle your
problem better than regression.  Specifically, I believe a decision tree
would do a better job of handling the interactions and categorical variable
(social support).  It would also yield a model (tree) that would be more
easily understandable than a pure mathematical function.

I am the author of a decision tree program called DTREG, and I would be
happy to run your data through DTREG for you to see how the tree model
compares with the regression model.

Phil Sherrod
.
.
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