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Re: st: Obtaining marginal effects and their standard errors after estimations with interactions
From
Richard Williams <[email protected]>
To
"[email protected]" <[email protected]>
Subject
Re: st: Obtaining marginal effects and their standard errors after estimations with interactions
Date
Fri, 4 Jan 2013 11:56:50 -0500
I hate trying to do something like this by hand. Too much room for
error. Can't you tell whoever you work for that you can't be expected
to work under such primitive inhumane conditions and you need Stata
12?
You might check out the user-written -inteff- command and see if it
helps. -margeff- is another user-written command that has various
advantages over -mfx-.
Sent from my iPad
On Jan 4, 2013, at 11:33 AM, Ebru Ozturk <[email protected]> wrote:
> Thank you, I use Stata 10 therefore I asked this question. I just wonder when we have more independent or control variables how do we adjust the given equations on this link: http://www.stata.com/support/faqs/statistics/marginal-effects-after-interactions/
>
> Kind regards
> Ebru
>
> ----------------------------------------
>> Date: Fri, 4 Jan 2013 09:32:25 -0500
>> To: [email protected]; [email protected]
>> From: [email protected]
>> Subject: Re: st: Obtaining marginal effects and their standard errors after estimations with interactions
>>
>> At 03:17 PM 1/3/2013, Ebru Ozturk wrote:
>>
>>> Dear All,
>>>
>>> On Stata FAQs' page, there are some given examples for Probit
>>> estimation with interaction effects for Stata 10 titled as "I am
>>> using a model with interactions. How can I obtain marginal effects
>>> and their standard errors?" and the link is:
>>> http://www.stata.com/support/faqs/statistics/marginal-effects-after-interactions/
>>>
>>> Do you think this way is still applicable to Probit estimation? and
>>> Is the below command correct when we have other independent or
>>> control variables?
>>
>> I don't know if you did it right or not, but if you have Stata 11 or
>> higher why not use -margins-, e.g.
>>
>> sysuse auto, clear
>> probit foreign weight length c.weight#c.length, nolog
>> margins, dydx(*)
>>
>>> local xb _b[weight]*`meanwei' + _b[len]*`meanlen' +
>>> _b[wl]*`meanwei'*`meanlen' + _b[C1]*C1+_b[C2]*C2 + _b[_cons] // if
>>> more variables //
>>>
>>> /////// example /////////
>>>
>>> sysuse auto, clear
>>> generate wl=weight*length
>>> probit foreign weight length wl, nolog
>>> quietly summarize weight if e(sample)
>>> local meanwei = r(mean)
>>> quietly summarize length if e(sample)
>>> local meanlen = r(mean)
>>>
>>> local xb _b[weight]*`meanwei' + _b[len]*`meanlen' +
>>> _b[wl]*`meanwei'*`meanlen' + _b[_cons]
>>> predictnl dydw = normalden(`xb')*(_b[weight]+ _b[wl]*`meanlen') in 1, se(sew)
>>> list dydw sew in 1
>>>
>>> predictnl dydl = normalden(`xb')*(_b[len]+ _b[wl]*`meanwei') in 1, se(sel)
>>> list dydl sel in 1
>>>
>>> predictnl dydlw =normalden(`xb')*(-(`xb'))*(_b[weight]+
>>> _b[wl]*`meanlen')*(_b[len]+ _b[wl]*`meanwei') + normalden(`xb')*(
>>> _b[wl]) in 1, se(selw)
>>> list dydlw selw in 1
>>>
>>> Ebru
>>
>> -------------------------------------------
>> Richard Williams, Notre Dame Dept of Sociology
>> OFFICE: (574)631-6668, (574)631-6463
>> HOME: (574)289-5227
>> EMAIL: [email protected]
>> WWW: http://www.nd.edu/~rwilliam
>>
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