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Re: st: How to model a positive continuous dependent variable with many zeros?


From   Hitesh Chandwani <hchandwani.stata@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: How to model a positive continuous dependent variable with many zeros?
Date   Thu, 2 Jun 2011 11:14:42 -0400

Adrian,

Do you mean: after
> modeling the zeros, model the non-zeros by deleting the zeros from
> the data set using the same predictors?......

Basically, yes. The first model will give you the probability of
having non-zero durations. This probability can then be multiplied
with estimates from the GLM to obtain an unbiased (more conservative)
estimate of mean seclusion duration.

I do have some references for two-part analyses...however, they all
deal with modeling cost data. I will email them to the listserv in a
few hours (once i get to my computer).

Sent from my iPhone

On Wed, Jun 1, 2011 at 2:38 AM, Adriaan Hoogendoorn
<aw.hoogendoorn@gmail.com> wrote:
> Thank you, Hithesh (and Maarten in a previous post), for your help.
> Your help is highly appreciated.
>
> The situation Maarten described appears exactly to be the case:
> Clinic staff members try reducing total seclusion durations (at the
> clinic level) by ending seclusions as soon as possible at the risk
> of introducing more seclusion episodes. Total seclusion duration
> (rated against the total time spent in the clinic) seems the
> appropriate quantity to evaluate seclusion policies. We find that
> total seclusion durations differ substantially across clinics. The
> explanation clinics give for having higher total seclusion durations
> than other clinics is that they claim to have “harder” patients, as
> Maarten suggested.
>
> Explaining these differences from patient characteristics (and some
> clinic characteristics) is exactly what this study is about.
>
> Your suggestion of combining the modeled zeros (from a logistic
> regression, or from the Poisson as Maarten suggested) with a model for
> non-zero duration (from GLM or Survival Analysis) seems very attractive.
> However, I have no experience on how to do this. Do you mean: after
> modeling the zeros, model the non-zeros by deleting the zeros from
> the data set using the same predictors?
>
> This would provide me with two sets of parameters. Do you think I can
> use these two sets of model parameters
> to estimate the total seclusion
> duration for a given ward with a given set of patients?
>
> I’ve never seen such a combined model in scientific literature – which
> may well be my mistake. Do you have any references how such a combination
> was applied and discussed?
>
> Kind regards,
> Adriaan W. Hoogendoorn
> GGZ inGeest, Amsterdam
>
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>



-- 
Hitesh S. Chandwani
University of Texas at Austin

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