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st: Re: xtmixed with log-transfered dependent variable: back to non-log on margins and marginsplot
From
"Joseph Coveney" <[email protected]>
To
<[email protected]>
Subject
st: Re: xtmixed with log-transfered dependent variable: back to non-log on margins and marginsplot
Date
Wed, 17 Apr 2013 11:06:31 +0900
Wensheng Sun wrote:
Hi, Please help. How to do post multilevel regression estimation after gllamm? I
tried "margins" command, it seems not work. Please fix it for me. Thanks.
[snip]
--------------------------------------------------------------------------------
You could try something like that below.
If a variable is not a factor variable (that is, if it is not included in the
model with the i.variable notation*), then it is considered by Stata to be a
continuous variable. So, despite its being coded 0/1, _I_girl_1 is considered
by Stata to be a continuous variable.
-margins- requires its first arguments to be factor variables--variables that
were in the model as i.variable. Because _I_girl_1 is a continuous variable and
not a factor variable, you must treat it as a continuous variable when you refer
to it with -margins-.
Joseph Coveney
*-anova- and -manova- are notable exceptions.
[Model fitting omitted for brevity. To see it, look at my most recent post in
this thread.]
. margins , at(_Igirl_1 = (0 1) age = (0(0.5)2.5))
Warning: cannot perform check for estimable functions.
Predictive margins Number of obs = 198
Model VCE : OIM
Expression : predict()
1._at : age = 0
_Igirl_1 = 0
2._at : age = 0
_Igirl_1 = 1
3._at : age = .5
_Igirl_1 = 0
4._at : age = .5
_Igirl_1 = 1
5._at : age = 1
_Igirl_1 = 0
6._at : age = 1
_Igirl_1 = 1
7._at : age = 1.5
_Igirl_1 = 0
8._at : age = 1.5
_Igirl_1 = 1
9._at : age = 2
_Igirl_1 = 0
10._at : age = 2
_Igirl_1 = 1
11._at : age = 2.5
_Igirl_1 = 0
12._at : age = 2.5
_Igirl_1 = 1
------------------------------------------------------------------------------
| Delta-method
| Margin Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_at |
1 | 1.828415 .042767 42.75 0.000 1.744593 1.912237
2 | 1.74101 .029594 58.83 0.000 1.683007 1.799013
3 | 1.99406 .0351737 56.69 0.000 1.925121 2.062999
4 | 1.906655 .0277658 68.67 0.000 1.852235 1.961075
5 | 2.159704 .0286555 75.37 0.000 2.103541 2.215868
6 | 2.072299 .0290146 71.42 0.000 2.015432 2.129167
7 | 2.325349 .0241011 96.48 0.000 2.278112 2.372586
8 | 2.237944 .0329929 67.83 0.000 2.173279 2.302609
9 | 2.490994 .0227236 109.62 0.000 2.446456 2.535531
10 | 2.403589 .0388715 61.83 0.000 2.327402 2.479775
11 | 2.656638 .0250527 106.04 0.000 2.607536 2.705741
12 | 2.569233 .0459263 55.94 0.000 2.479219 2.659247
------------------------------------------------------------------------------
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