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Re: st: RE: AW: Sample selection models under zero-truncated negative binomial models


From   sjsamuels@gmail.com
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: AW: Sample selection models under zero-truncated negative binomial models
Date   Tue, 2 Jun 2009 13:21:27 -0400

A potential problem with Jon's original approach is that the use of
services is an event with a time dimension--time to first use of
services.  People might not use services until they need them.
Instead of a logit model (my preference also),   a survival model for
the first part might be appropriate.


With later first-use, the time available for later visits is reduced,
and  number of visits might be associated with the time from first use
to the end of observation.  Moreover, people with later first-visits
(or none) might differ in their degree of  need for subsequent visits.

To account for unequal follow-up times,  I suggest a supplementary
analysis in which the outcome for the second part of the hurdle model
is not the number of visits, but the rate of visits (per unit time at
risk).

-Steve.

On Tue, Jun 2, 2009 at 12:22 PM, Lachenbruch, Peter
<Peter.Lachenbruch@oregonstate.edu> wrote:
> This could also be handled by a two-part or hurdle model.  The 0 vs. non-zero model is given by a probit or logit (my preference) model.  The non-zeros are modeled by the count data or OLS or what have you.  The results can be combined since the likelihood separates (the zero values are identifiable - no visits vs number of visits).
>
> Tony
>
> Peter A. Lachenbruch
> Department of Public Health
> Oregon State University
> Corvallis, OR 97330
> Phone: 541-737-3832
> FAX: 541-737-4001
>
>
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Martin Weiss
> Sent: Tuesday, June 02, 2009 7:02 AM
> To: statalist@hsphsun2.harvard.edu
> Subject: st: AW: Sample selection models under zero-truncated negative binomial models
>
>
> <>
>
> Try
>
> *************
> ssc d cmp
> *************
>
>
>
> HTH
> Martin
>
>
> -----Ursprüngliche Nachricht-----
> Von: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von John Ataguba
> Gesendet: Dienstag, 2. Juni 2009 16:00
> An: Statalist statalist mailing
> Betreff: st: Sample selection models under zero-truncated negative binomial
> models
>
> Dear colleagues,
>
> I want to enquire if it is possible to perform a ztnb (zero-truncated
> negative binomial) model on a dataset that has the zeros observed in a
> fashion similar to the heckman sample selection model.
>
> Specifically, I have a binary variable on use/non use of outpatient health
> services and I fitted a standard probit/logit model to observe the factors
> that predict the probaility of use.  Subsequently, I want to explain the
> factors the influence the amount of visits to the health facililities. Since
> this is a count data, I cannot fit the standard Heckman model using the
> standard two-part procedure in stata command -heckman-.
>
> My fear now is that my sample of users will be biased if I fit a ztnb model
> on only the users given that i have information on the non-users which I
> used to run the initial probit/logit estimation.
>
> Is it possible to generate the inverse of mills' ratio from the probit model
> and include this in the ztnb model? will this be consistent? etc...
>
> Are there any smarter suggestions?  Any reference that has used the similar
> sample selection form will be appreciated.
>
> Regards
>
> Jon
>
>
>
>
>
>
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