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: [email protected]
> [mailto:[email protected]] On Behalf Of Visintainer,
> Paul
> Sent: Monday, April 21, 2008 12:01 PM
> To: [email protected]
> 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: [email protected]
> [mailto:[email protected]] 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
>
>
>
>
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