st: Obtaining marginal effects and their standard errors after estimations with interactions

[Ebru Ozturk <ebru_0512@hotmail.com>]

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?

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 		 	   		  
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