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# Re: st: estimating a proportion in panel data

 From Lloyd Dumont To statalist@hsphsun2.harvard.edu Subject Re: st: estimating a proportion in panel data Date Wed, 13 Oct 2010 08:49:29 -0700 (PDT)

```Thank you for this, Maarten.  Can you (or anyone else) suggest a good primer on running and interpreting residual diagnostics for multilevel data?  Rabe-Hesketh and Skrondal just barely touch on it.  Lloyd

--- On Tue, 10/12/10, Maarten buis <maartenbuis@yahoo.co.uk> wrote:

> From: Maarten buis <maartenbuis@yahoo.co.uk>
> Subject: Re: st: estimating a proportion in panel data
> To: statalist@hsphsun2.harvard.edu
> Date: Tuesday, October 12, 2010, 12:28 PM
> --- On Tue, 12/10/10, Lloyd Dumont
> wrote:
> > Mainly, I am estimating a proportion [0,1].  That
> is,
> > it is a continuous variable between zero and one,
> > inclusive.
> >
> > #1
> > The data are panel data.  Think of it as a
> proportion
> > observed for each unit each month, over many months.
> >
> > #2
> > My focal independent variable is a two-way
> multiplicative
> > interaction term.  I know there are a number of
> issues
> > associated with estimating these interactions in
> logits and
> > probits.
>
> I would just go for a linear panel model (-xtreg-) and
> carefully check the following:
> - are the effects of continuous predictors linear or is
> the
>   logical boundary of 0 and 1 forcing non-linearity in
> the
>   effect?
> - are the error term and random effects normally
> distributed
>   with constant variance or are the logical boundaries
> causing
>   trouble?
>
> This boils down to looking at the residuals in a way one
> should
> do anyhow when doing such an analysis, except that now we
> have
> a specific suspicion what the problem might be, which makes
> it
> easier to spot such problems.
>
> Hope this helps,
> Maarten
>
> --------------------------
> Maarten L. Buis
> Institut fuer Soziologie
> Universitaet Tuebingen
> Wilhelmstrasse 36
> 72074 Tuebingen
> Germany
>
> http://www.maartenbuis.nl
> --------------------------
>
>
>
>
>
>
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```