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Re: st: 3D plot for interaction effects


From   James Bernard <jamesstatalist@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: 3D plot for interaction effects
Date   Thu, 24 Jan 2013 10:08:38 +0800

Thanks Billy,
-marginsplot- was not a solution

On Wed, Jan 23, 2013 at 8:16 PM, William Buchanan
<william@williambuchanan.net> wrote:
> The have you tried working with -margins- and -marginsplot- after fitting your model?  I would check that out as a possibility first.
>
> HTH,
> Billy
>
> Sent from my iPhone
>
> On Jan 23, 2013, at 2:37, James Bernard <jamesstatalist@gmail.com> wrote:
>
>> Hi all,
>>
>> I am struggling with plotting main effect and interaction effect of my
>> negative-binomial model... I though Stata might have something, given
>> the popularity of these plots among empiricists
>>
>>
>>
>> This is a a fixed effect negative binomial model.... I have pace as my
>> main ID, Pace-squared, then an interaction term "Scale" and then
>> interaction of that variable with Pace and Pace-Squared.
>>
>>
>> I want to draw this where my DV is on the vertical axis and main plot
>> on the X and then interaction on Y (like a surface plot). I wonder if
>> this can be done in Stata, given that negative binomial is a nonlinear
>> model....
>>
>>
>> ----------------------------------------------------------------------------------------
>>          lagpatent_f1 |      Coef.   Std. Err.      z    P>|z|
>> [95% Conf. Interval]
>> -----------------------+----------------------------------------------------------------
>>               Pace      |   1.494223   .5783452     2.58   0.010
>> .3606869    2.627758
>>            Pace^2      |  -.6852545   .2394282    -2.86   0.004
>> -1.154525   -.2159839
>>        Scale            |   .0563032   .3031137     0.19   0.853
>> -.5377887     .650395
>> Pace*Scale          |  -1.551876   .8982472    -1.73   0.084
>> -3.312408    .2086566
>> Pace*Scale^2        |    .849984   .4441609     1.91   0.056
>> -.0205553    1.720523
>>
>>                 _cons |   .5746716   .2601009     2.21   0.027
>> .0648832     1.08446
>>
>>
>> Many Thanks,
>> james
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