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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