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Re: st: correct for selection bias in survival analysis


From   Antoine Terracol <Antoine.Terracol@univ-paris1.fr>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: correct for selection bias in survival analysis
Date   Wed, 05 May 2010 13:06:55 +0200

Bonjour Marguerite,

as Maarten said earlier, including the IMR will not work in your setting because the second stage is not linear, and also because the IMR rests on the bivariate normality assumption, and your duration model has a log-logistic distribution.

To my knowledge, there is no "simple" (as in "a couple of lines of code") way to correct for selection biais in duration models in Stata. You will need to write your own likelihood function, the simplest way to do it would be to assume a log-normal distribution for the duration model, and a Probit for the selection stage, taking advantage of the bivariate normality of your error terms. For more general setups, you may want to have a look at

Prieger, J. E. "A flexible parametric selection model for non-normal data with application to health care usage" Journal of Applied Econometrics, 2002, 17(4), 367-392

In addition, it seems you actually have a kind of double hurdle model with two successive selection stages: having had a civil war and, conditional on civil war, that peace was settled.

Given your research question, I assume you do not have many data points, so you should try to stick to the simplest setup possible, and forget about the double selection...

Antoine

PS: I have some old code for the log-normal duration model with selection, feel free to send me an email privately if you're interested in it (ou de passer à la MSE dans le courant de la semaine prochaine)

On 05/05/2010 12:44, Marguerite Duponchel wrote:
I am working on the duration of post civil war peace so I want to correct for
the fact that my sample is restricted to countries who 1/had a civil war, 2/
the peace was settled.

Thanks.

Quoting Maarten buis<maartenbuis@yahoo.co.uk>:

--- On Wed, 5/5/10, Marguerite Duponchel wrote:
It's just that as I am the one creating the selection bias
on a full available sample, I thought there might be a way
to correct it while using the info in the complete data
which frailty would not integrate.

The easiest solution is not to make the selection or, if you
want to work with a smaller dataset, make the selection
random. Otherwise I don't understand why you would want to
make a selection and than "correct" for the fact that you
made a selection.

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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Marguerite Duponchel

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