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From |
"Visintainer, Paul" <PAUL_VISINTAINER@NYMC.EDU> |

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

Subject |
st: RE: Stratify analysis - logistic regression with dummies |

Date |
Thu, 5 Jun 2008 10:49:26 -0400 |

Ricardo, The difference is probably due to the fact that you are developing your models on different samples sizes, and as a consequence, a different mean age for each sample. This isn't a problem when you are computing an unadjusted OR for a categorical variable. (Compare your unadjusted -logit- command with the equivalent -tabodds- command. In your example, your first logit command -xi: logistic low i.race- is computing the ORs for a 3x2 table. You can replicate the logit command by running -tabodds low race, or-). When you add age as a continuous variable to your model AND use the "if" statement, your model is alternatively excluding observations who are either RACE2 or RACE3, thus your sample size changes (e.g, n=122 or n=163). The adjustment for age is based on the mean age for sample being used to estimate the OR. Thus, as you change the samples change so does the mean age: For n=189: mean age== 23.2381 For n=163: mean age== 23.5092 (no RACE2) For n=122: mean age== 23.7049 (no RACE3) -p ______________________________________ Paul F. Visintainer, PhD Department of Epidemiology and Biostatistics School of Public Health New York Medical College PH: (914) 594-4804 FX: (914) 594-4853 -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Ricardo Ovaldia Sent: Wednesday, June 04, 2008 10:15 AM To: statalist@hsphsun2.harvard.edu Subject: st: Stratify analysis - logistic regression with dummies I am confused by some of the result that I got. I will illustrate using Hosmer & Lemeshow' low weight data: . use http://www.stata-press.com/data/r10/lbw.dta (Hosmer & Lemeshow data) if I fit . xi:logistic low i.race and then fit . xi:logistic low i.race if race==1 | race==2 and . xi:logistic low i.race if race==1 | race==3 I get the same OR for _Irace_2 and _Irace_3 as I do for the full model. This is as expected because the dummies are ortogonal to each other. However, when a covariate is added to the model, the same is not true anymore: . xi:logistic low i.race age low | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------- --- _Irace_2 | 2.106974 .9932407 1.58 0.114 .8363679 5.307878 _Irace_3 | 1.767748 .6229325 1.62 0.106 .8860686 3.526738 age | .9612592 .0311206 -1.22 0.222 .9021588 1.024231 ------------------------------------------------------------------------ --- . xi:logistic low i.race age if race==1 | race==2 ------------------------------------------------------------------------ --- low | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------- --- _Irace_2 | 2.155207 1.021287 1.62 0.105 .8513944 5.45566 age | .9705512 .0376446 -0.77 0.441 .8995039 1.04721 ------------------------------------------------------------------------ --- . xi:logistic low i.race age if race==1 | race==3 ------------------------------------------------------------------------ --- low | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------- --- _Irace_3 | 1.724551 .6098827 1.54 0.123 .8622856 3.449063 age | .9440875 .0340586 -1.59 0.111 .8796392 1.013258 ------------------------------------------------------------------------ --- There is no missing data. I am very confused about which OR to reports and what are the differences in these models. I was not expecting these results. Thank you in advance, Ricardo. Ricardo Ovaldia, MS Statistician Oklahoma City, OK * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: RE: Stratify analysis - logistic regression with dummies***From:*Ricardo Ovaldia <ovaldia@yahoo.com>

**References**:**st: Stratify analysis - logistic regression with dummies***From:*Ricardo Ovaldia <ovaldia@yahoo.com>

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