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st: RE: "if" statement
...
The xi command creates the dummies before the logistic command runs, so
it drops ageg==2.
The -if age>=30- drops ageg==2, so there are now too many dummies, so
the logistic command drops one - ageg==4.
Try placing -char ageg[omit] 3- in front of the logistic commands
______________________________________________
Kieran McCaul MPH PhD
WA Centre for Health & Ageing (M573)
University of Western Australia
Level 6, Ainslie House
48 Murray St
Perth 6000
Phone: (08) 9224-2701
Fax: (08) 9224 8009
email: [email protected]
http://myprofile.cos.com/mccaul
http://www.researcherid.com/rid/B-8751-2008
______________________________________________
If you live to be one hundred, you've got it made.
Very few people die past that age - George Burns
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Victor
Mauricio Herrera
Sent: Thursday, 17 September 2009 4:44 AM
To: statalist
Cc: Leonelo Bautista
Subject: st: "if" statement
I'd appreciate if somebody could explain the following behavior of the
"if" statement when used with "logistic" (I'm running STATA IC/10.1).
webuse nhanes2f
gen ageg=2 if age>=20 & age<30
replace ageg=3 if age>=30 & age<40
replace ageg=4 if age>=40 & age<50
replace ageg=5 if age>=50 & age<60
replace ageg=6 if age>=60 & age<70
replace ageg=7 if age>=70
replace sex=0 if sex==2
model 1 --> xi: logistic sex i.ageg
i.ageg _Iageg_2-7 (naturally coded; _Iageg_2
omitted)
Logistic regression Number of obs =
10337
LR chi2(5) =
2.80
Prob > chi2 =
0.7302
Log likelihood = -7150.626 Pseudo R2 =
0.0002
------------------------------------------------------------------------
------
sex | Odds Ratio Std. Err. z P>|z| [95% Conf.
Interval]
-------------+----------------------------------------------------------
------
_Iageg_3 | .9761655 .0632659 -0.37 0.710 .8597191
1.108384
_Iageg_4 | .9971218 .0696639 -0.04 0.967 .8695188
1.143451
_Iageg_5 | .9424283 .065592 -0.85 0.394 .8222534
1.080167
_Iageg_6 | .9903392 .0554211 -0.17 0.862 .8874609
1.105144
_Iageg_7 | .8963705 .0683978 -1.43 0.152 .7718562
1.040971
------------------------------------------------------------------------
------
model 2 --> xi: logistic sex i.ageg if age>=30
i.ageg _Iageg_2-7 (naturally coded; _Iageg_2
omitted)
note: _Iageg_4 dropped because of collinearity
Logistic regression Number of obs =
8017
LR chi2(4) =
2.35
Prob > chi2 =
0.6713
Log likelihood = -5544.1939 Pseudo R2 =
0.0002
------------------------------------------------------------------------
------
sex | Odds Ratio Std. Err. z P>|z| [95% Conf.
Interval]
-------------+----------------------------------------------------------
------
_Iageg_3 | .9789833 .0734452 -0.28 0.777 .8451164
1.134055
_Iageg_5 | .9451487 .0748512 -0.71 0.476 .8092619
1.103853
_Iageg_6 | .9931979 .0670654 -0.10 0.919 .8700789
1.133739
_Iageg_7 | .8989579 .0765455 -1.25 0.211 .7607821
1.06223
------------------------------------------------------------------------
------
Why is the age group 4 (40-49) dropped due to collinearity if there are
610 males and 660 females in this stratum? More worrisome, why is the
age group 2 (20-29) still being used as reference when it should have
been dropped as a consequence of the "if" statement (i.e. _Iage_3 should
be the reference instead of _Iage_2)?
model 3 --> xi: logistic sex i.ageg if age<70
i.ageg _Iageg_2-7 (naturally coded; _Iageg_2
omitted)
note: _Iageg_7 dropped because of collinearity
Logistic regression Number of obs =
9352
LR chi2(4) =
0.86
Prob > chi2 =
0.9303
Log likelihood = -6472.0855 Pseudo R2 =
0.0001
------------------------------------------------------------------------
------
sex | Odds Ratio Std. Err. z P>|z| [95% Conf.
Interval]
-------------+----------------------------------------------------------
------
_Iageg_3 | .9761655 .0632659 -0.37 0.710 .8597191
1.108384
_Iageg_4 | .9971218 .0696639 -0.04 0.967 .8695188
1.143451
_Iageg_5 | .9424283 .065592 -0.85 0.394 .8222534
1.080167
_Iageg_6 | .9903392 .0554211 -0.17 0.862 .8874609
1.105144
------------------------------------------------------------------------
------
Now the "if" statement seems to work fine, as subjects with age>=70 are
excluded (i.e. the _Iage_7 group has been dropped!)
This also occurs if I run these models using STATA IC/9.2 or if one
models another dichotomous variable using a different dataset.
Many thanks,
VICTOR M. HERRERA MD. MS.
Research Assistant
Population Health Sciences Department
University of Wisconsin
610 Walnut St. 626 WARF
Madison, WI 53726
(608) 265-3686
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