Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.
[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]
Re: st: Propensity score matching after multiple imputation
From
William Buchanan <[email protected]>
To
"[email protected]" <[email protected]>
Subject
Re: st: Propensity score matching after multiple imputation
Date
Fri, 21 Mar 2014 09:13:49 -0500
Please use full references as you are asked in the Statalist FAQ. Also, the purpose of MI is to find plausible values for variables where the mechanism leading to the missingness is known or can be approximated with a model. So, why would you estimate the propensity scores (which would use list wise deletion), and then impute values afterwards? Given that Donald Rubin is both an authority on propensity score methods and multiple imputation, I'd imagine you could find some helpful guidance in some of his work.
HTH,
Billy
Sent from my iPhone
> On Mar 21, 2014, at 7:41, natalia malancu <[email protected]> wrote:
>
> Hi guys!
>
> After reading Mitra, Robin and Reiter, Jerome P. (2011) and Hill's
> 2004 paper, I was wondering whether there is a way to:
> a. compute and then
> b. average propensity scores after multiple imputation. Causal
> inference to follow
>
> In STATA 12, which I am using, this is not possible with psmatch2. Is
> is possible in STATA 13 with teffects? Are there are options I am
> missing on?
>
> Any suggestions are much appreciated,
> Natalia
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/faqs/resources/statalist-faq/
> * http://www.ats.ucla.edu/stat/stata/
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/faqs/resources/statalist-faq/
* http://www.ats.ucla.edu/stat/stata/