Re: propensity score for 3 treatments

Posted by Mike on Nov 30, 2012; 3:39pm
URL: http://spssx-discussion.165.s1.nabble.com/propensity-score-for-3-treatments-tp5716540p5716549.html

Donald Rubin at Columbia reviews propsensity scoring for two and three
groups in this article:

http://www.stat.columbia.edu/~gelman/stuff_for_blog/propensity.html

Quoting from the article:

|With more than two treatment conditions, the propensity score usually
|differs for each pair of treatment groups being compared (that is, with
|three treatment groups labelled A, B, and C, there are three propensity
|scores: A compared with B, A compared with C, and B compared with C).
|At first, this may seem to be a limitation of propensity score technology
|relative to a model-based analysis, but in fact it is an important strength
|and points to further weaknesses in a model-based approach. We show
|this by exploring a range of hypothetical modifications to Cochran's [2]
|smoking example.

Rubin, D. B. (1997). Estimating causal effects from large data sets using
propensity scores. Annals of internal medicine, 127, 757-763.

Given that this is a 1997 publication, it is reasonable to assumed that
there are more recent articles that might be relevant, such as the following:

http://europepmc.org/articles/PMC3105164/pdf/nihms276566.pdf

-Mike Palij
New York University
[hidden email]

On Fri, Nov 30, 2012 at 10:11 AM, Maguin, Eugene <[hidden email]> wrote:

> I first thought of an ordinal regression but then realized that there is no assurance that the parallel lines assumption would be met and then switched to multinomial regression. Maybe this is not a problem but the usual propensity setup has matching on the computed logit or log odds value from a logistic regression with a dichotomous DV. But with a three category DV you get two computed logits or log odds values irrespective of whether you use ordinal or multinomial. So how is the matching to be done.
>
> You've got to figure that this problem has come up before and an accepted method has been developed; however, I don't know what it is. My suggestion is to average the logits and match on that (but check the resulting match to see how well the match is on each logit value). My rationale is that if you formed matched triplets and assigned them to condition then did the multinomial regression analysis, each member of the triplet would have the same average logit and logit components.
>
> Gene Maguin
>
> -----Original Message-----
> From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of Bruce Weaver
> Sent: Friday, November 30, 2012 9:39 AM
> To: [hidden email]
> Subject: Re: propensity score for 3 treatments
>
> Multinomial logistic regression (NOMREG)?
>
>
>
> la volta statistics wrote
>> Hi all
>>
>> To control for confounding bias from non-random treatment assignment
>> with
>> 3
>> different treatments, I would like to calculate a propensity score I
>> later can use in a cox regression model. I know the procedures for a
>> two-treatment approach (logistic regression). But how would I
>> calculate such a score when I have three treatments?
>>
>>
>>
>> Thanks in advance
>>
>> Christian
>>
>>
>>
>>
>>
>> **********************************
>> la volta statistics
>> Christian Schmidhauser, Dr.phil.II
>> Weinbergstrasse 108
>> CH-8006 Zürich
>> Tel: [phone]
>> Fax: [phone]
>> email:  &lt;mailto:
>
>> schmidhauser@
>
>> &gt; mailto:
>
>> schmidhauser@
>
>>
>> Web:  &lt;http://www.lavolta.ch&gt; www.lavolta.ch
>
>
>
>
>
> -----
> --
> Bruce Weaver
> [hidden email]
> http://sites.google.com/a/lakeheadu.ca/bweaver/
>
> "When all else fails, RTFM."
>
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>
> --
> View this message in context: http://spssx-discussion.1045642.n5.nabble.com/propensity-score-for-3-treatments-tp5716540p5716544.html
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