Unfortunately, I don't think we have an automated procedure for everything. You would have to multiply impute the data, do matching on each imputed data set, and then combine it in zelig() using mi() function. But this does not require any programming. You can simply run the same matching procedure on each data set via matchit() and then feed the resulting multiple matched data sets into zelig().
Good luck,
Kosuke
Department of Politics
Princeton University
http://imai.princeton.edu
On Sep 13, 2011, at 6:02 PM, Pingaul jb wrote:
> Dear Professor,
> I’m a post-doctoral student at Montreal University. I’m actually in Columbia, working and propensity scores with a colleague and using MatchIt and Zelig. First, congratulations for your packages that are very flexible.
>
> My question is about multiple imputation and propensity scores with these softwares. From what I understand, combining both approaches would include:
>
> 1/ Doing multiple imputation and testing which variables to include.
>
> 2/ Propensity score analysis on each imputed data set and pooling the overall balance to check if it is ok (or on each data set?).
>
> 3/ Calculation of the quantities of interest for each data set
>
> 4/ Pooling the quantities across data sets.
>
> I would like to know if there is a written syntax to perform the MatchIt analysis for all of the imputed data set without having to do it manually and check the overall balance. Also, in theory, the number of individuals retained after propensity score matching and the weights can be different for each imputed data set. So that we have to perform the final analysis on each one and then pool the data with a specific procedure to take into account the eventual varying Ns? I normally use Mice package for multiple imputation but it seems that Zelig handle Amelia. My colleague seems to do be able to do all that in stata, but I’m not sure how to make all the three R packages work together.
>
> I would be very happy if you could indicate to me a reference or a place where I can find the syntax to do that (I’ve been using R for some times so I can use packages easily but I have no programming skills).
>
>
> Best Regards!
>
>
>
> Jean-Baptiste
>
-
Zelig Mailing List, served by Harvard-MIT Data Center
Send messages: zelig(a)lists.gking.harvard.edu
[un]subscribe Options: http://lists.gking.harvard.edu/?info=zelig
Zelig program information: http://gking.harvard.edu/zelig/
Hi,
It doesn't seem like "robust=TRUE" is working for linear regression (ls). The standard errors are coming out exactly the same as with "robust=FALSE".
I am on R 3.0.0 and Zelig 4.1-3 (and have tried on Linux and Windows).
Has anyone else had this problem?
Here's a reproducible example:
## "Robust" estimation not working
require(Zelig)
df <- data.frame(y=c(rnorm(n=100, mean=0, sd=1), rnorm(n=100, mean=10, sd=10)),
x=c(rep(1, 100), rep(2,100)))
z.robustT <- zelig(y ~ x, data=df, model="ls", robust=TRUE)
z.robustF <- zelig(y ~ x, data=df, model="ls", robust=FALSE)
# Standard errors are the same:
summary(z.robustT)
summary(z.robustF)
## Alternative
require(sandwich)
require(lmtest)
lm.robustF <- lm(y ~ x, data=df)
summary(lm.robustF) #matches z.robustF
vcovMat <- vcovHC(lm.robustF)
lm.robustT <- coeftest(lm.robustF, vcov.=vcovMat)
lm.robustT #same coef, different se
##########
Rod
<table width="100%" border="0" cellspacing="0" cellpadding="0" style="width:100%;">
<tr>
<td align="left" style="text-align:justify;"><font face="arial,sans-serif" size="1" color="#999999"><span style="font-size:11px;">This communication is intended for the addressee only. It is confidential. If you have received this communication in error, please notify us immediately and destroy the original message. You may not copy or disseminate this communication without the permission of the University. Only authorised signatories are competent to enter into agreements on behalf of the University and recipients are thus advised that the content of this message may not be legally binding on the University and may contain the personal views and opinions of the author, which are not necessarily the views and opinions of The University of the Witwatersrand, Johannesburg. All agreements between the University and outsiders are subject to South African Law unless the University agrees in writing to the contrary. </span></font></td>
</tr>
</table
