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RE: st: xtgee for skewed data

From   "Lachenbruch, Peter" <[email protected]>
To   "[email protected]" <[email protected]>
Subject   RE: st: xtgee for skewed data
Date   Fri, 26 Aug 2011 09:55:28 -0700

If there is an identifiable reason for the zeros, you could use a two-part model.  If not, you have a mixture disstribution with some unknown fraction (to be estimated!) of zeros.  There is an issue of Statistic Methods in Medical Research from 2002 that discusses this.

From: [email protected] [[email protected]] On Behalf Of Nick Cox [[email protected]]
Sent: Thursday, August 25, 2011 4:15 AM
To: [email protected]
Subject: Re: st: xtgee for skewed data

The discussion started by William Gould at

seems relevant. You have a massive spike in the distribution. No
transformation will much affect that, as by Murphy's theorem a spike
maps to a spike, and in any case there would be the usual argument
about what to do with zeros. However, (importantly different here)  a
logarithmic link might help a lot.

The key substantive issue is whether all the people with zeros really
belong in the same model as the others.


On Thu, Aug 25, 2011 at 11:56 AM, Andre Siqueira
<[email protected]> wrote:

> I’d like some opinions about how to build a model of a very skewed data
> (parasitemia) using GEE.
> My data consist of repeated measures of parasitemia of many individuals
> (some of them having only one measurement and others having up to five) I’d
> like to assess the association with a 4-level exposures adjusted for 3
> covariates. Only 5% of the measurements had a value above zero.
> I’ve already discussed with some people who told me not to transform the
> data and analyse it with a normal distribution, so I’ve built the following
> model but I’m still in doubt if it’s the best way to do it:
> Xtgee parasitemia i.main_exp i.co_var1 i.co_var2 i.co_var3, i(id)
> vce(robust)

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