Hello,
I'm working in R, and trying to understand the decision, post-matching,
between using model = 'linear' and model = 'linear-RE' in the specification
of att(), like this:
##
data(LL)
todrop <- c("treated","re78")
# cem match: automatic bin choice
mat <- cem(treatment="treated", data=LL, drop="re78")
mat
# models
att(mat, re78 ~ treated, data=LL, model = 'linear')
att(mat, re78 ~ treated, data=LL, model = 'linear-RE')
The SATT is a bit different across models, but what's really striking is
how relatively tiny the standard errors are when model = 'linear-RE'.
Is there something I could read on the motivation behind 'linear-RE',
contexts where it might be appropriate, etc.?
Thank you,
Juan Tellez
--
Juan Fernando Tellez
http://juanftellez.com
Department of Political Science
Duke University
Good morning,
I am using CEM for the first time and going through the Blackwell, Iacus, King, and Porro (2009) article in the Stata Journal by following the commands. However, I cannot get the imbalance command to work. I receive the following error message:
. imbalance age education black nodegree re74, treatment(treated)
command imbalance is unrecognized
r(199);
Has there been an update to the Stata commands since this article was published?
Any guidance would be greatly appreciated.
Thank you,
Ann
________________________
Ann Cisney-Booth, Ph.D.
Senior Administrator
Strategic Data Project Fellow
Research and Evaluation
445 W. Amelia St.; Orlando, FL 32801
(407) 317-3200 ext. 200-2545
www.ocps.net<http://www.ocps.net/>
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