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Re: st: ZOIB procedure


From   Prerna S <maruiprerna@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: ZOIB procedure
Date   Mon, 19 Sep 2011 19:30:14 -0400

Thanks for your responses, Maarten and Cam. I haven't yet had a chance
to get hold of all the suggested references yet but I feel more
informed of potential ways to deal with my dataset on stata.

Prerna


On 19 September 2011 09:43, Maarten Buis <maartenlbuis@gmail.com> wrote:
> On Mon, Sep 19, 2011 at 3:12 PM, Cameron McIntosh wrote:
>> For proportions, Warton et al. (2011) recommend a logit transformation to achieve linearity. You could then run a linear model in -gllamm-, while allowing cov(e1,e2) and back-transform the predicted values (yhats).
>
> You do not have to use -gllamm- for that, use -mvreg- instead. In that
> case you are using Aitchison's (2003) method.
>
>> Exponentiating these should return the geometric mean value of the yhats, and the geometric mean and median are (asymptotically) equivalent.
>
> That is not quite correct, you will get the geometric mean if you log
> transform your dependent variable, and afterwards exponentiate the
> mean. With the logit transformation the back-transform is fairly
> meaningless. See the example below:
>
> *------------ begin example ----------------
> sysuse auto, clear
> sum price, meanonly
> gen pprice = (price - r(min) ) /(r(max) - r(min))
> gen logit = logit(pprice)
> gen log = ln(pprice)
>
> ameans pprice
> sum  logit, meanonly
> di invlogit(r(mean))
> sum log, meanonly
> di exp(r(mean))
> *------------ end example ----------------
> (For more on examples I sent to the Statalist see:
> http://www.maartenbuis.nl/example_faq )
>
> -- Maarten
>
> Aitchison (2003) The Statistical Analysis of Compositional Data.
> Caldwell, NJ: The Blackburn Press.
>
> --------------------------
> Maarten L. Buis
> Institut fuer Soziologie
> Universitaet Tuebingen
> Wilhelmstrasse 36
> 72074 Tuebingen
> Germany
>
>
> http://www.maartenbuis.nl
> --------------------------
>
> *
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>

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