My apologies. For some reason the previous message was truncated and I have been having difficulty resending this message. I have included the output.
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From: [email protected]
To: [email protected]
Subject: subpop question
Date: Sat, 24 Jan 2009 20:14:35 -0800
Statalist:
I am fitting a logistic regression model using svy in Stata version 9.
I am trying to use the subpop option to focus on only those adults 55
and older. However, in my logistic model I specifically want to look at
the differences among age categories for participation in adult
education (aepart) so I also have age categories (AgeCat7) as an
independent variable. I have received messages on my output that
indicate putting in age will cause problems. My questions are:
1. Below is my output, note _IAgeCat7_7 dropped due to collinearity.
This is the category for anyone under 55 so it shouldn't have been in
the model, but does this message indicate another problem?
2. I
have also run the model with 6 category age just coding age less than
55 as missing but this seems akin to misusing if commands instead
of the subpop with svy.
Can someone tell me how to include age
in the model but also focus on the subpopulation of interest accounting
for the survey design? Thank you, Carissa
xi: svy, subpop(agesub): logistic aepart i.AgeCat7 i.Incomequ i.HIGHEDUC employed female
i.AgeCat7 _IAgeCat7_1-7 (naturally coded; _IAgeCat7_1 omitted)
i.Incomequart _IIncomequa_1-4 (naturally coded; _IIncomequa_1 omitted)
i.HIGHEDUC _IHIGHEDUC_1-4 (naturally coded; _IHIGHEDUC_1 omitted)
(running logistic on estimation sample)
note:_IAgeCat7_7 dropped due to collinearity
Survey: Logistic regression
Number of strata = 2
Number of obs = 8904
Number of PSUs = 8806
Population size = 2.116e+08
Subpop. no. of obs = 3649
Subpop. size = 62989418
Design df = 8804
F( 13, 8792)= 21.57
Prob> F = 0.0000
------------------------------------------------------------------------------
| Linearized
aepart | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IAgeCat7_2 |1.128364 .1712264 0.80 0.426 .8380377 1.519269
_IAgeCat7_3 |.8190012 .1358204 -1.20 0.229 .5917043 1.133612
_IAgeCat7_4 |.8138198 .1540807 -1.09 0.277 .5614976 1.179529
_IAgeCat7_5 |1.050606 .2072118 0.25 0.802 .7137293 1.546486
_IAgeCat7_6 |.5036011 .0968218 -3.57 0.000 .3454723 .7341085
_IIncomequ~2| 1.415502 .2227664 2.21 0.027 1.03976 1.927027
_IIncomequ~3| 1.448079 .2233722 2.40 0.016 1.070219 1.959348
_IIncomequ~4| 2.326815 .3547075 5.54 0.000 1.725774 3.137182
_IHIGHEDUC_2| 2.016762 .3553085 3.98 0.000 1.427813 2.848643
_IHIGHEDUC_3| 3.010628 .8260452 4.02 0.000 1.758229 5.15512
_IHIGHEDUC_4| 4.172463 .7755193 7.69 0.000 2.89842 6.006532
employed |2.189151 .2617844 6.55 0.000 1.731701 2.767443
female |2.234095 .2508465 7.16 0.000 1.792729 2.784124
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