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Re: st: calculation of marginal effect

From   Maarten Buis <>
Subject   Re: st: calculation of marginal effect
Date   Wed, 29 Aug 2012 11:02:49 +0200

--- On Tue, Aug 28, 2012 at 8:39 PM, Yanru Qiao wrote me privately:
> We analysis the  the racial disparities in health care area, Like,
> blacks(whites) who are not eligible for a health care program are more
> likely to be sick than those who are eligible under different health
> care utilization measurements . And here is an example of my
> code(bnh--black, main06--eligible for program):
> svy: logit goodhealth i.bnh##i.main06, or nolog
> margins, over (bnh main06) expression (exp(xb()))  post
> lincom 0.bnh#0.main06-1.bnh#0.main06
> lincom 0.bnh#1.main06-1.bnh#1.main06
> lincom (0.bnh#0.main06-1.bnh#0.main06)-(0.bnh#1.main06-1.bnh#1.main06)
> My question is:
> 1.Can I use expression (exp(xb()))  to all other models? Like
> [R]regress [R]mlogit [R]nbreg?
> 2.How to interpret the marginal effect in a multinomial logistic
> regression (Like: we have five categories)

Such questions need to be sent to Statalist instead of individual
members. The reasons for that are discussed in

The code you quote comes from M.L. Buis (2010) "Stata tip 87:
Interpretation of interactions in non-linear models", The Stata
Journal, 10(2), pp. 305-308. The real point of that Stata tip is that
you should _not_ use marginal effects to interpret interactions but
odds ratios instead. So that is going to be the meta-answer to your
questions: If you have interactions, just forget about marginal
effects and learn to interpret your model in terms of the natural
metric of that model.

Ad. 1: No

Ad. 2: <>

-- Maarten

Maarten L. Buis
Reichpietschufer 50
10785 Berlin
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