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st: ordinal mixed effects model with interaction and quadratic terms
From
"Pritsch, Julian" <[email protected]>
To
"'[email protected]'" <[email protected]>
Subject
st: ordinal mixed effects model with interaction and quadratic terms
Date
Fri, 28 Mar 2014 19:59:18 +0000
Dear statalist-users,
I am estimating a ordinal multilevel model using the -meologit- command. My dependent variable has 4 categories (0-3).
In my Level-1 model I introduced a dummy for sex (sex) and a z-standardized version of age (agez). Additionally, I introduced and z-standardized squared-term of age (age_sqz) because I want to show non-linear effects of age on my DV.
My question is twofold:
(1) I want to introduce an interaction term of sex & agez: Do I also need to form an interaction term of sex and the squared version of agez to specify my model correctly?
(2) After estimating my model I would like to find out (using the -marginsplot- command), if there are any differences between male and female respondents regarding the age effect.
Regarding question (2) I tried the following:
---------------------code-----------------------------------------------
*for outcome(0)
margins sex, at(agez=(-1.88 -1.19 0.01 1.11 1.85)) vsquish ///
level(99) ///
predict(outcome(0) fixedonly)
--------------------------------------------------------------------------
*Note: the values for agez are the 2/15/50/85/98-percentile to represent -2SD/-1SD/ 0 /+1SD/+2SD
I repeat that syntax for every outcome(0,1,2,3) and will try to combine the graphs.
Is there a more elegant way to do this? And what about the interaction of sex and the squared term of age (age_sqz)
Any advice would be appreciated.
Julian
_________________
Julian Pritsch, Dipl.-Soz.
Max-Planck-Institut für ausländisches
und internationales Strafrecht
Günterstalstraße 73
79100 Freiburg i. Br.
Tel.: +49 (761) 7081-291
e-Mail: [email protected]
homepage: www.mpicc.de
Max-Planck-Institute for Foreign
and International Criminal Law
Guenterstalstrasse 73
79100 Freiburg i. Br.
Germany
Phone: +49 (761) 7081-291
e-Mail: [email protected]
homepage: www.mpicc.de
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