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From |
"Kieran McCaul" <Kieran.McCaul@uwa.edu.au> |

To |
<statalist@hsphsun2.harvard.edu> |

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: Kieran.McCaul@uwa.edu.au 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: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Tina Hernandez-Boussard Sent: Friday, 4 September 2009 1:54 AM To: statalist@hsphsun2.harvard.edu 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 * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**RE: st: regression using dummy variables***From:*Maarten buis <maartenbuis@yahoo.co.uk>

**st: regression using eform***From:*Tina Hernandez-Boussard <boussard@stanford.edu>

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