Re: st: ordinal mixed effects model with interaction and quadratic terms

[David Hoaglin <dchoaglin@gmail.com>]

Julian,

Your model should contain the interaction between sex and age_sqz.
The syntax suggested by Darcy may be one way to do it, though I think
you z-standardized age-squared, rather than squaring z-standardized
age.

What is the evidence (in the data) that the nonlinear effects of age
are quadratic (or reasonably well approximated by a quadratic)?
Nonlinear effects can take a variety of forms, and many (perhaps most)
of those forms are not quadratic.  You may be able to get your data to
point toward a suitable nonlinear form for age.

David Hoaglin

On Fri, Mar 28, 2014 at 3:59 PM, Pritsch, Julian <j.pritsch@mpicc.de> wrote:
> 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
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