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Re: st: xtmixied: Marginal Effect with Interactions


From   Guy Grossman <guygrossman1@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: xtmixied: Marginal Effect with Interactions
Date   Mon, 30 Aug 2010 14:38:50 +0000

Thank you Maarten! This works perfectly, and is exactly what I was looking for.
Guy

On Mon, Aug 30, 2010 at 9:43 AM, Maarten buis <maartenbuis@yahoo.co.uk> wrote:
>
> --- On Sun, 29/8/10, Guy Grossman wrote:
> > I am using Stata 10.1 on Mac to estimate the following
> > model:
> >
> > xtmixed change x1 x2 x1Xx2 c1 c2 c3 c4 c5  || group:
> > || id:, mle nolog
> >
> > in which both x1 and x2 are dummies and x1 is a treatment
> > variable in a randomized experiment. I have two questions:
> >
> > 1. how can I calculate the effect of x1 conditional on
> > x2==1, while setting the control variables to their mean
> > (continuous variables) or median (categorical)?
>
> -xtmixed- is a linear model so there is no need to fix the
> other covariates, as the marginal effect will be the same
> regardless of what value you fix them at. Since x2 is a
> dummie, x1 has basically two effects: the effect when
> x2 is 0 and the effect when x2 is 1. The former is just the
> coefficient of x1 the latter is the coefficient of x1 +
> the coefficient of x1Xx2. You can use -lincom- for that.
> See -help lincom- and the example below.
>
> > 2. what do you suggest would be the best way to graphically
> > present the results given that both x1 and x2 are dummies?
>
> Below is one sugestion:
>
> *---------------- begin example -----------------
> webuse productivity, clear
> // create some dummies and the interaction variable
> sum private, meanonly
> gen x1 = private > r(mean)
> sum emp, meanonly
> gen x2 = emp > r(mean)
> gen x1Xx2 = x1*x2
>
> // estimate the model
> xtmixed gsp x1 x2 x1Xx2 hwy water other unemp || region: || state:, mle
>
> // get the effect of x1 when x2 == 1
> lincom x1 + x1Xx2
>
>
> // turn the estimates into variables, so they
> // can be graphed
> gen x = 1 in 1
> gen y = r(estimate) in 1
> gen lb = y - invnormal(0.975)*r(se) in 1
> gen ub = y + invnormal(0.975)*r(se) in 1
>
> replace x = 0 in 2
> replace y = _b[x1] in 2
> replace lb = y - invnormal(0.975)*_se[x1] in 2
> replace ub = y + invnormal(0.975)*_se[x1] in 2
>
> // the graph
> twoway scatter y x ||                   ///
>       rcap lb ub x,                    ///
>       xlab(0 1)                        ///
>       xscale(range(-.5 1.5))           ///
>       xtitle(x2)                       ///
>       ytitle(effect x1)                ///
>       legend(order(1 "effect"          ///
>                    2 "conf. interval"))
> *---------------- end example ------------------
> (For more on examples I sent to the Statalist see:
> http://www.maartenbuis.nl/example_faq )
>
> Hope this helps,
> Maarten
>
> --------------------------
> Maarten L. Buis
> Institut fuer Soziologie
> Universitaet Tuebingen
> Wilhelmstrasse 36
> 72074 Tuebingen
> Germany
>
> http://www.maartenbuis.nl
> --------------------------
>
>
>
>
> *
> *   For searches and help try:
> *   http://www.stata.com/help.cgi?search
> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/



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