Re: re:st: pscore question

[Dan Kimmel <dkimmel@uchicago.edu>]

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.

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



On Thu, Feb 17, 2011 at 12:36 PM, Ariel Linden, DrPH
<ariel.linden@gmail.com> wrote:
>
> 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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