One minimal, minuscule, minute, microscopic extra gloss --
as the point arises in many other posts --
is to point out that Mills' ratio is named for J.P. Mills.
John P. Mills. 1926.
Table of the Ratio: Area to Bounding Ordinate, for Any Portion of Normal Curve.
Biometrika 18, 3/4, 395-400
Depending on your preferences or prejudices on proper punctuation,
different renderings are possible. Mills ratio, Mills' ratio and
Mills's ratio all seem defensible to me.
But either "Mill's" or "mills" is, strictly, wrong.
Nick
[email protected]
Maarten buis
> I have a couple of comments, but no ready to use solution:
> o If I remember correctly the use of the inverse mills ratio
> is derived
> from the assumption that both the error in the selection
> equation and
> in the equation of interest are normal. In that case I wouldn't use
> the IMR with -mlogit-.
> o You don't give a proper citation for the ``paper by Glewwe'', so I
> can't look it up and give you advise on that.
> o Models that deal with similar problems have been discussed in the
> special issue of the Stata Journal in 2006 on simulated maximum
> likelihood, The Stata Journal volume 6 issue 2.
> o multinomial probit relaxes the IIA assumption if you allow for
> correlation between error terms, but these models are typically
> harder
> to estimate, so I would start with multinomial logit and
> only move to
> multinomial probit if necesary.
> o Are you sure you don't have a double selection process going on?
> Selecetion equation 1: is there a fever? Selection equation
> 2: Do you
> have acces to modern healthcare? (if not there isn't much of choice)
> Finally the model of interest: do you go to public,
> private, or other
> healthcare institutions?
Thuilliez Josselin <[email protected]> wrote:
> > I would like to estimate a multinomial logit or multinomial probit
> > model with
> > sample selection. The selection equation is based on a simple Logit
> > or Probit
> > model. I have 3 questions.
> >
> > Firstly, since there is only Heckprob in Stata I was wondering
> > whether
> > it would be correct to do the following:
> > a- estimate the selection equation using Logit or Probit
> > b- calculate the inverse Mill's ratio
> > c- use the IMR as a regressor in the second-stage multinomial logit
> > or
> > probit model
> >
> > Secondly, if this is incorrect: how can I do? Is there a stata
> > program
> > that allow to take into account selection bias in
> multinomial models?
> > I have seen a paper of Glewwe (3-choice multinomial probit with
> > selectivity corrections) but it does not provide any solution for
> > programing this in Stata.
> >
> > Thirdly, if there is a way to solve this problem, is it
> better to use
> > the multinomial Logit or the multinomial Probit. Is it possible for
> > instance, to relaxe the IIA assumption using the multinomial probit
> > and at the same time correcting for the selection bias?
> >
> > The object of the study is to determine the determinants of
> > healthcare
> > seeking behaviour for children with fever in developing countries.
> > My data looks like:
> > First choice: Dummy variable for fever: 0 (no fever) / 1(fever)
> > Second choice:
> > 0 No acces to modern healthcare (reference category)
> > 1 Public health facility
> > 2 Private health facility
> > 3 Other medical facility
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