If your question really is about A, then why do you need B in here at
all? And why do you need A^2? If C is categorical, then there is not
much sense in saying "Introducing C shifts A to the right". You could
say that for different levels of C the conditional distributions of A
are different, and that can be checked with ANOVA or its
non-parametric versions (Kruskal-Wallis). Please clarify what your
research questions here is.
On Tue, Oct 20, 2009 at 3:56 PM, P K <[email protected]> wrote:
> Hi,
>
> I am trying to examine the moderating effects on a curvilinear relation between variable A and B in a multiple regression,
>
> ie.
>
> A ->B : positive coeff.
> A^2 ->B : negative coefficient
>
>
> I want to examine whether introducing variable C shifts the whole distribution of A to the right.
>
> Variable A and B are continuous
> Variable C is categorical.
>
> For examing such a moderating role of variable C, I think that only the interaction of AxC has to be significant and positive - is that right?
>
> Or does the interaction betwen A^2 xC also has to be significant (in that case, this would imply that the distribution of A is not only shifted to the right, but also that the shape of the distribution has changed, correct?)
>
> Any advice is appreciated.
> Thanks,
> Pat
>
>
>
>
>
>
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>
--
Stas Kolenikov, also found at http://stas.kolenikov.name
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