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From |
Svend Juul <SJ@soci.au.dk> |

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

Subject |
Re: st: epiconf: counfounding |

Date |
Wed, 9 Feb 2011 10:34:28 +0100 |

SR Millis wrote: I've been working with your Stata program, epiconf. Using theaccompanying dataset and fitting the following logistic regression model: . epiconf dead ab_uria, con(age weight) cat(hichol hypert smoke sex) backward I obtained the following results. How do you interpret the model when the changes in the absolute values of the change in the odds ratios are not monotonically increasing (in the case of backward selection) or, in the case of forward selection, monotonically decreasing? That is, in this model, if we take 10% as the cut-point of importance, we need only adjust for age, smoking, and weight? If so, how do you obtain the adjusted rate ratio and its confidence interval? Assessment of Confounding Effects Using Change-in-Estimate Method Outcome: "dead" Exposure: "ab_uria" N = 743 Backward approach Potential confounders were removed one at a time sequentially Adj Var 95% CI Change in OR p Crude 2.35 1.24, 4.44 . . -i.sex 2.26 1.21, 4.24 -3.6 0.47664 -i.hichol 2.08 1.12, 3.86 -8.0 0.15144 -weight 1.88 1.04, 3.40 -10.0 0.21915 -i.hypert 2.00 1.13, 3.55 6.6 0.42812 -i.smoke 2.24 1.28, 3.92 11.9 0.06456 -age* 3.90 2.34, 6.52 74.4 0.00000 *Crude estimate =================================================================== First comment: Don't. Data-driven model building leads to wrong conclusions; see, for example, this FAQ: http://www.stata.com/support/faqs/stat/stepwise.html Using a change-in-estimate criterion is no better than using a significance criterion. Second comment: Obviously, the "Crude" estimate in the first line is not the crude estimate, but the starting estimate, and with backward selection it is the model including all variables. If you (for legitimate reasons) want to adjust for age, smoking, and weight: . logistic dead ab_uria age i.smoke weight or, if your Stata is prior to version 11: . xi: logistic dead ab_uria age i.smoke weight Svend ________________________________________________________ Svend Juul School of Public Health, Department of Epidemiology Bartholins Allé 2 DK-8000 Aarhus C, Denmark sj@soci.au.dk<mailto:sj@soci.au.dk> _________________________________________________________ * * 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/

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