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Re: st: Multinomial logits with proportions for dependent variables


From   "Clive Nicholas" <Clive.Nicholas@newcastle.ac.uk>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Multinomial logits with proportions for dependent variables
Date   Wed, 31 Aug 2005 05:57:23 +0100 (BST)

Some time ago, Greg Lee wrote:

> According to some econometrics texts (e.g. Greene's Econometric
> Analysis), in multinomial logit models the dependent variable can be
> specified as proportions adding up to one (as in the case where
> consumers predict their probabilities of purchasing various products)
> instead of using 0/1 inputs (when you know what they chose).
>
> So, to clarify, I have J possible dependent options, and respondents are
> attaching a possibility chance of choosing that option to each one. I
> then wish to analyse this via multinomial or conditional logistic
> regression.
>
> Does anyone know if STATA can analyse this? From what I have seen looking
> around it requires 0 or 1 inputs, but I stand open to correction

I've never heard of a such model, I have to say. One (not entirely
satisfactory) fix would be to use Jack Buckley's -mlbeta- routine, which
models dependent variables-as-proportions as if they were
beta-distributed, using maximum likelihood to generate the parameter
estimates. This is _not_ available from SSC, so to download it within
Stata:

. net from http://www2.bc.edu/~bucklesj

and then click on -mlbeta-.

The limitation here is, of course, that the probabilities of each outcome
would have to be modelled separately, rather than together, as you want.
Perhaps somebody else has a better solution.

I hope this helps.

CLIVE NICHOLAS        |t: 0(044)7903 397793
Politics              |e: clive.nicholas@ncl.ac.uk
Newcastle University  |http://www.ncl.ac.uk/geps

Whereever you go and whatever you do, just remember this. No matter how
many like you, admire you, love you or adore you, the number of people
turning up to your funeral will be largely determined by local weather
conditions.

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