Hi! Is there a good example (reference, chapter, article) of how to use propensity score matching (PSM) or propensity score estimation (PSE) with structural equation modeling in MPLUS? Thank you so much, Clara
Here is an answer from a colleague in the causal inference field:
The short answer is that no, I donít know of a good reference for propensity scores with SEM.
The longer answer is that I think in part I donít know of a good reference for this because the goals of the two methods are somewhat different, at least from what I understand about SEM. From my understanding SEM is designed for looking at relationships between a large number of variables (and not necessarily always in a causal way). Propensity scores are designed when you really just have one variable of interest (the ďtreatmentĒ) and you want to look at the treatmentís effects on some outcome(s), basically treating all of the other variables as nuisance confounders. So the methods donít necessarily generally fit together very well. As one specific example, there has been very limited work using propensity scores in the context of post-treatment variables and mediation, but that is still basically a very simple type of SEM (if one even wants to think about it in that way at all).
I should add that there is at least one example of research that uses propensity scores as an explanatory variable in an SEM setting. You can email me if you want me to give you more information on that.
Can you send it to me? Your email is not available. Thanks so much Clara
Emil Coman posted on Wednesday, August 08, 2012 - 7:06 am
Don't want to boast, but I will: I presented recently this: Coman E., Yanovitzky I., Coman M., Weeks M. R. (2012). Understanding propensity score matching through a more flexible causal modeling alternative. Mixture and multilevel causal modeling of true effects. 2012 Modern Modeling Methods (M3) Conference. http://www.modeling.uconn.edu/ They have not posted my PPT yet, so I can email it.