Date:         Tue, 19 Sep 2006 04:50:36 -0700
Reply-To:     IK <bigdoctor2004@GMAIL.COM>
Sender:       "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:         IK <bigdoctor2004@GMAIL.COM>
Organization: http://groups.google.com
Subject:      Re: difference between regression coefficients in non-nested
Comments: To: sas-l@uga.edu
Content-Type: text/plain; charset="iso-8859-1"

I want to be able to make statements regarding which variable X1 or x2
is a better predictor of Y.  I tried to use both variables in a nested
regression but cos of multicoll. issues I cant.

i forgot to add - my data is market data - returns and earnings and for
the most part most of the underlying assumptions have not been
violated.  i used proc reg initially but then when i couldnt compare
the slopes i included a predicted variable for Y in model 1 and used
proc autoreg and did the same for model 2 i.e. a davidson and mackinnon
test.  am i out to lunch on all this?

thanks


David L Cassell wrote:
> bigdoctor2004@GMAIL.COM wrote:
> >
> >I have some difficulty solving the following problem: I have an
> >independent var (y) and 2 ind. var (x1 and X2). I am running two
> >non-nested regressions and I want to compare the betas from regression
> >1 with X1 and regression 2 with X2.  any help on how to do this is
> >appreciated.
>
> Let me see if I have this straight.
>
> You have two models.  Model 1 looks like this:
>
>     model y = x1;
>
> and model 2 looks like this:
>
>     model y = x2;
>
> Is that right?
>
> If so, then what you are asking does not make any sense.
> I advise you not to try to compare the slopes.  And don't try
> to compare the standardized betas either.
>
> Why aren't you look at nested models?  Then you would be
> able to see the contribution of one variable, over and above
> what the first one does.  You don't even need to do this as
> two separate models.
>
> And what proc are you using?  Have you made sure that all
> the underlying assumptions are valid?  Where do your data come
> from?  These are all relevant quesitons which may alter the
> advice offered.
>
> HTH,
> David
> --
> David L. Cassell
> mathematical statistician
> Design Pathways
> 3115 NW Norwood Pl.
> Corvallis OR 97330
>
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