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From |
"Lachenbruch, Peter" <Peter.Lachenbruch@oregonstate.edu> |

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

Subject |
RE: st: trend in ORs across ordered levels of a 3rd variable |

Date |
Mon, 21 Apr 2008 15:56:10 -0700 |

This sounds like a task for logistic regression using the confounder and the risk factor. If you want to see if there's effect modification, use the product of the risk factor and confounder. You may want to categorize these variables. Tony Peter A. Lachenbruch Department of Public Health Oregon State University Corvallis, OR 97330 Phone: 541-737-3832 FAX: 541-737-4001 -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Visintainer, Paul Sent: Monday, April 21, 2008 12:01 PM To: statalist@hsphsun2.harvard.edu Subject: RE: st: trend in ORs across ordered levels of a 3rd variable Joseph, Thanks for your input. But I don't think -epitab- addresses this question. The output you provided gives the trend in ORs "adjusting" for the confounder. What I wanted to know is whether we can detect a linear pattern of the ORs over levels of the confounder (which, to me, looks like a specific type of interaction) Another example: suppose I want to know whether there is a difference in the risk (odds) of death between males and females from trauma. Suppose my third variable is level of consciousness (ordinal variable measured at 4 levels). Say, my output shows that as level of consciousness decreases, the OR for gender and death increases: (e.g., ORs at each level of consciousness: 1.0 at level 1, 1.5 at level 2, 1.9 at level 3, and 2.3 at level four), which suggests that men do worse at lower levels of consciousness. I suppose that one way to address this is to approach it as if consciousness were a continuous variable, then look at the slopes for consciousness in logit models run separately for men and women. I can't think of any other approach. -p ______________________________________ Paul F. Visintainer, PhD School of Public Health New York Medical College -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Joseph Coveney Sent: Saturday, April 19, 2008 3:21 AM To: Statalist Subject: Re: st: trend in ORs across ordered levels of a 3rd variable Paul Visintainer wrote: Is there an approach to analyzing the trend in odds ratios across the ordered levels of a 3rd variable? For example, Suppose I have the risk of obesity in high school students by gender over three different grades: Grade OR 10 1.5 11 1.9 12 2.2 There is a test of homogeneity to determine whether these ORs differ across grade strata. Is there a test to determine whether the pattern is linear across strata? ------------------------------------------------------------------------ -------- Are you looking for something other than -tabodds-? Joseph Coveney . webuse bdesop . tabodds case alcohol [fweight = freq], or ------------------------------------------------------------------------ --- alcohol | Odds Ratio chi2 P>chi2 [95% Conf. Interval] -------------+---------------------------------------------------------- --- 0-39 | 1.000000 . . . . 40-79 | 3.565271 32.70 0.0000 2.237981 5.679744 80-119 | 7.802616 75.03 0.0000 4.497054 13.537932 120+ | 27.225705 160.41 0.0000 12.507808 59.262107 ------------------------------------------------------------------------ --- Test of homogeneity (equal odds): chi2(3) = 158.79 Pr>chi2 = 0.0000 Score test for trend of odds: chi2(1) = 152.97 Pr>chi2 = 0.0000 * * 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/

**References**:**Re: st: trend in ORs across ordered levels of a 3rd variable***From:*"Joseph Coveney" <jcoveney@bigplanet.com>

**RE: st: trend in ORs across ordered levels of a 3rd variable***From:*"Visintainer, Paul" <PAUL_VISINTAINER@NYMC.EDU>

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