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

From   "Visintainer, Paul" <PAUL_VISINTAINER@NYMC.EDU>
To   <>
Subject   RE: st: trend in ORs across ordered levels of a 3rd variable
Date   Mon, 21 Apr 2008 15:00:53 -0400


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.


Paul F. Visintainer, PhD
School of Public Health
New York Medical College

-----Original Message-----
[] On Behalf Of Joseph
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.
        0-39 |    1.000000          .           .              .
       40-79 |    3.565271      32.70       0.0000      2.237981
      80-119 |    7.802616      75.03       0.0000      4.497054
        120+ |   27.225705     160.41       0.0000     12.507808
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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