[R] interpretation for multiple regression

Daniel Malter daniel at umd.edu
Sun Nov 11 22:55:59 CET 2007


Hi,

maybe I don't understand your question correctly, but I don't see a reason
why there should be a significant interaction term at all.

To the question why you regression is linear in B and C:

your regressor B is linear (in B), i.e. B= 1B.
your regressor C is some quadratic function of B, i.e. C=cB^2

As I see it, your C captures the quadratic form of the relationship between
B and A. The relationship between C and A should therefore be linear in the
regression because your C already captures the quadratic form. I.e. your C
"cloaks" the significant relationship, because C is itself a quadratic
function of B.

Does that make any sense? Or did I understand your question incorrectly?
Daniel


-------------------------
cuncta stricte discussurus
-------------------------

-----Ursprüngliche Nachricht-----
Von: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] Im
Auftrag von Rolf Turner
Gesendet: Sunday, November 11, 2007 4:06 PM
An: Irene Mantzouni
Cc: r-help at stat.math.ethz.ch
Betreff: Re: [R] interpretation for multiple regression


On 10/11/2007, at 3:48 AM, Irene Mantzouni wrote:

> Dear all,
>
> probably this is quite clear for most of you but for me it is a 
> headache...
>
> I am regressing response A against the continuous covariate B and the 
> relationship is clearly quadratic.
> When I add a second covariate B, the relationship becomes linear for 
> both B and C.
> So, I expect that the interaction of B:C should also be significant, 
> which is not the case.
> How do you interpret this??


	Suppose A = a*B + b*C  and C = c*B^2.

	Then A = a*B + b*c+B^2 --- quadratic in B.

	But the original relationship, predicting A from B and C, is simply
linear in B and C,
	no interaction term.

	Clear enuff?

		cheers,

			Rolf Turner

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