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st: AW: Logistic function


From   "Martin Weiss" <martin.weiss1@gmx.de>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: AW: Logistic function
Date   Thu, 18 Jun 2009 18:35:30 +0200

<> 

You should use the c.d.f. of the logistic distribution which you can obtain here: http://en.wikipedia.org/wiki/Logistic_distribution



HTH
Martin


-----Ursprüngliche Nachricht-----
Von: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von John Ataguba
Gesendet: Donnerstag, 18. Juni 2009 18:21
An: Statalist statalist mailing
Betreff: st: Logistic function

Dear users,

This question might sound simple or silly.

I have been trying to generate marginal effects after a logit regression with interactions.  Becasue there are several interactions, I cannot use the -inteff- command.

I know that I can use the -predictnl- command but I have problems here in specifying the logistic function.

Below is an example of the case for a probit model with interaction:

probit foreign trunk mpg  d  /*note that d is a dummy*/
qui sum  trunk
sca _tt=r(mean)
qui sum  mpg
sca mg=r(mean)

local xb1 (_b[_cons]+ _b[trunk]*_tt + _b[mpg]*mg + _b[d]*1)
local xb0 (_b[_cons]+ _b[trunk]*_tt + _b[mpg]*mg + _b[d]*0)

predictnl dfdd=normal(`xb1')-normal(`xb0') in 1, se(serr)
list dfdd serr  in 1

My question is: what density function do I specify for the logistic function if I use a logit instead of a probit?

Any suggestion will be welcomed.

Regards

Jon 


      


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