Re: re:st: pscore question

["Ariel Linden, DrPH" <ariel.linden@gmail.com>]

Hi Dan,

Modeling any outcome can be done using propensity score methods. However,
what I am not clear on here is if the treatment variable in multilevel (or
even continuous). 

While not the easiest of reads, I suggest you read: Robins JM, Hernán MA,
Brumback B. Marginal structural models and causal inference in epidemiology.
Epidemiol 2000;11:550?60. 

In particular, section 6 discusses multilevel treatment. In general, you
would use an ordinal or multilogit model to estimate the propensity score,
and then use the estimate corresponding to  true level of the treatment.

For a continuous treatment variable (e.g. a drug with increasing dosage),
modelling the propensity score is even more complex. Fortunately, there is a
user written stata program available called -doseresponse- , (but you really
would only need the sub-routine called -gpscore-)  

This program comes with an accompanying paper in the Stata Journal by
Michela Bia and Alessandra Mattei called "A STATA Package for the Estimation
of the Dose-Response Function through Adjustment for the Generalized
Propensity Score",  2008. Stata Journal Volume 8 Number 3.  

I hope this helps

Ariel

From: Dan Kimmel <dkimmel@uchicago.edu>
Subject: Re: re:st: pscore question

Dear Statalisters,

Thanks for your suggestions re: my pscore question.  I am now
encountering another problem, which was (indeed) my reason for not
simply using psmatch2 in the first place: does anyone know if there is
a way to use psmatch2 (or some other propensity score module) to model
a nominal- or ordinal-scale outcome?  I am attempting to predict the
effect of exposure to violence in school on students' health outcomes,
where health is measured with a simple 5-category subjective response.
 Thanks,

Dan
- --
Daniel M. Kimmel
Department of Sociology
University of Chicago
917.696.2597




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