Date:         Thu, 29 Nov 2007 15:58:37 -0500
Reply-To:     Sigurd Hermansen <HERMANS1@WESTAT.COM>
Sender:       "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:         Sigurd Hermansen <HERMANS1@WESTAT.COM>
Subject:      Re: Statistical test for difference between two numbers
Comments: To: Abhay Kaushik <abhaykaushik@HOTMAIL.COM>
In-Reply-To:  <200711292006.lATHZsd2022760@mailgw.cc.uga.edu>
Content-Type: text/plain; charset="us-ascii"

The test you are proposing should, it seems to me, compare F values (or
better indicators of model fit) of the model that includes the variable
d and the model that doesn't. If omitting d does not reduce model fit,
then pooling data will not reduce the explanatory or predictive power of
the model.

Rejecting or failing to reject the null hypothesis of that test won't
make estimates or predictions of the model any less biased or estimate
the variance or prediction of the model any more accurately. No matter
how many sightings you take from a single point, or whether sighted to
one side or another, a telescope won't let you see what's behind a barn.
S
-----Original Message-----
From: owner-sas-l@listserv.uga.edu [mailto:owner-sas-l@listserv.uga.edu]
On Behalf Of Abhay Kaushik
Sent: Thursday, November 29, 2007 3:07 PM
To: SAS-L@LISTSERV.UGA.EDU
Cc: Abhay Kaushik
Subject: Re: Statistical test for difference between two numbers


Hi All,
Thanks for your suggestions. There is another method that I tried and it
works. Since my two data sets are identical but types. So I added them
together as a one big file and created dummy based on type. Then I run
OLS and also added another line in my OLS regression:

test intercept = intercept+d;
F value of this tells whether the two intercepts are ststistically
different.