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Re: re:st: pscore question
Dan Kimmel <email@example.com>
Re: re:st: pscore question
Thu, 17 Feb 2011 12:54:57 -0600
Hello Ariel (et al),
My treatment is binomial -- it is just an indicator of whether the
respondent has experienced violence at school. However, since
students at different schools have different risks of violence
exposure, I estimated the propensity score using an HLM. (I suppose I
could do this with a dose-response model, but I'm having enough
trouble as it is.)
My outcome, however -- the variable on which I want to see if violence
exposure has any effect -- is an ordinal measure of general health
("excellent," "very good," "good," "fair," "poor"). I was originally
trying to stratify the observations into blocks, balanced on their
propensity scores and all other covariates, and then run a simple
ordinal regression model with block ID dummies. However, I used quite
a number of covariates, and since I don't know of a way to estimate a
multilevel model using pscore or psmatch2, calculating the strata by
hand became prohibitively difficult. psmatch2 uses propensity scores
calculated from an outside program, but (as far as I can tell) seems
to assume that the outcome is continuous.
I will take a look at the article you recommend. Thanks for the tip.
Any further suggestions are still, of course, welcome.
Daniel M. Kimmel
Department of Sociology
University of Chicago
On Thu, Feb 17, 2011 at 12:36 PM, Ariel Linden, DrPH
> 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
> From: Dan Kimmel <firstname.lastname@example.org>
> 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.
> - --
> Daniel M. Kimmel
> Department of Sociology
> University of Chicago
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