# st: RE: regression using eform

 From "Kieran McCaul" <[email protected]> To <[email protected]> Subject st: RE: regression using eform Date Fri, 4 Sep 2009 05:15:58 +0800

...

I agree with Clive's comment regarding the use of step-wise regression.

More to the point, however, why do you think that exponentiating the
coefficients from a linear regression will give you odds ratios?

______________________________________________
Kieran McCaul MPH PhD
WA Centre for Health & Ageing (M573)
University of Western Australia
Level 6, Ainslie House
48 Murray St
Perth 6000
Phone: (08) 9224-2701
Fax: (08) 9224 8009
email: [email protected]
http://myprofile.cos.com/mccaul
http://www.researcherid.com/rid/B-8751-2008
______________________________________________
If you live to be one hundred, you've got it made.
Very few people die past that age - George Burns

-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Tina
Hernandez-Boussard
Sent: Friday, 4 September 2009 1:54 AM
To: [email protected]
Subject: st: regression using eform

Hi,

I have a question regarding a regression model that I am running.  I
am looking at predictors for a variable slope, which is growth of a
tumor per day.  I have ran this model and using

sw, pr(.2):regress slope smoker exercise bmi , eform(odds)

I have reran the model, only multiplying the slope by 365.25 to get
the growth per year.  I did not think that this would change
anything, yet it changes the odds ratios.  I still get the same
prob>f, r-squared, and adjusted r-squared.  However, model and
residual ss, df, and ms are different.

Can someone please explain why my odds ratios are changing, yet the t
and P>|t| are not?

First model:
------------------------------------------------------------------------

---
slope |       odds   Std. Err.      t    P>|t|     [95% Conf.
Interval]
-------------
+----------------------------------------------------------------
exercise |   1.000341   .0001396     2.45   0.017
1.000062     1.00062
bmi |   .9999843   9.47e-06    -1.66   0.102     .
9999653    1.000003
smoker |   1.000748   .0003167     2.36   0.021
1.000116    1.001382

Model with slope*365.25:

------------------------------------------------------------------------

------
growth |       odds   Std. Err.      t    P>|t|     [95% Conf.
Interval]
-------------
+----------------------------------------------------------------
exercise  |   1.132765   .0577325     2.45   0.017
1.023043    1.254254
bmi |   .9942751   .0034406    -1.66   0.102     .
9874212    1.001177
smoker |   1.314259   .1519301     2.36   0.021
1.043092    1.655921

Thanks,

Tina
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