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From |
"Dr. med. Berthold Hoppe" <berthold.hoppe@charite.de> |

To |
statalist@hsphsun2.harvard.edu |

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

Date |
Tue, 22 Apr 2008 12:37:28 +0200 (CEST) |

The problem seems to be similiar to one I am actually faced with. Have you tried an analyses like this: logit death consc if sex==0 est store A logit death consc if sex==1 est store B suest A B test [A]consc=[B]consc Berthold > 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/ > * * 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: trend in ORs across ordered levels of a 3rd variable***From:*Maarten buis <maartenbuis@yahoo.co.uk>

**RE: st: trend in ORs across ordered levels of a 3rd variable***From:*Maarten buis <maartenbuis@yahoo.co.uk>

**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>

**RE: st: trend in ORs across ordered levels of a 3rd variable***From:*"Lachenbruch, Peter" <Peter.Lachenbruch@oregonstate.edu>

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