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st: Date: Wed, 30 Apr 2003 15:42:26 -0400


From   "Daniel, Gregory" <GDaniel@healthcore.com>
To   "'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu>
Subject   st: Date: Wed, 30 Apr 2003 15:42:26 -0400
Date   Wed, 30 Apr 2003 15:42:49 -0400 (EDT)

Dear Statalist,

I am running a logistic model where I have discovered interactions between:

1) Gender [male] and Age [age_65; dichotomous]; and
2) Angioplasty [idx_angio] and Age [age_65]

My confusion is in interpreting the simple effects of age at each level of
the interactions.  
I have tried using a.age_65@g.idx_angio with i.male*i.age_65 also present in
the model, but was not able to interpret the results. 


For example:


. xi3: logistic outcome  i.male*i.age_65  a.age_65@g.idx_angio 

i.male            _Imale_0-1          (naturally coded; _Imale_0 omitted)
i.age_65          _Iage_65_0-1        (naturally coded; _Iage_65_0 omitted)
g.idx_angio       _Iidx_angio_0-1     (naturally coded; _Iidx_angio_0
omitted)

note: _Iag1Wid1 dropped due to collinearity

Logistic regression                               Number of obs   =
15877
                                                  LR chi2(5)      =
403.64
                                                  Prob > chi2     =
0.0000
Log likelihood = -10093.725                       Pseudo R2       =
0.0196

----------------------------------------------------------------------------
--
Outcome      | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf.
Interval]
-------------+--------------------------------------------------------------
--
    _Imale_1 |   1.312062   .0609901     5.84   0.000     1.197807
1.437215
  _Iage_65_1 |   1.277411   .2022554     1.55   0.122     .9366081
1.742221
   _Ima1Xag1 |   .7752202   .0525718    -3.75   0.000     .6787355
.8854206
_Iidx_angi~1 |   2.334687   .2707346     7.31   0.000     1.860038
2.930459
   _Iag1Wid0 |   1.603602    .249047     3.04   0.002     1.182772
2.174164
----------------------------------------------------------------------------
--


Where _Iag1Wid1 = over65 vs. under65 at idx_angio==1; and _Iag1Wid0 = over65
vs. under65 at idx_angio==0

Why was _Iag1Wid1 dropped due to collinearity?  Also is the OR for _Imale_1
(1.31) for "males versus females AT under 65 (age_65==0)"? --Or is it "males
versus females AT under 65 AND no angioplasty (idx_angio==0)"?

Also, I have tried the 3 way interaction: i.male*i.age_65*i.idx_angio, but
none of the terms were significant.


What am I missing here??



Gregory Daniel
Health Core, Inc.
4735 Ogletown-Stanton Road
Suite 3201
Newark, DE 19713-2094
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