25 Jul
2016
25 Jul
'16
6:20 p.m.
Hi Alisa, you have either an approximately randomized experimental or,
equivalently, an observational (nonexperimental) study. CEM usually works
well in that situation.
Gary
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*Gary King* - Albert J. Weatherhead III University Professor - Director,
IQSS <http://iq.harvard.edu/> - Harvard University
GaryKing.org - King(a)Harvard.edu - @KingGary <https://twitter.com/kinggary> -
617-500-7570 - Assistant <king-assist(a)iq.harvard.edu>du>: 617-495-9271
On Mon, Jul 25, 2016 at 3:55 PM, Padon, Alisa A <alisa.padon(a)asc.upenn.edu>
wrote:
Hi,
I have a few questions regarding using CEM on an already randomized sample
that I would appreciate any help with.
Briefly, I conducted an online experiment in which we randomized
respondents to 1 of 3 conditions. After exposure, some respondents dropped
out before the final outcome measures. In total, I have 417 respondents who
completed the full study, but because of the drop-outs, there is unequal
distribution of some key variables between conditions.
My questions are:
1) Would CEM be an appropriate solution to an unequal condition problem
like this?
2) Does the use of the method invalidate the randomization?
3) Is there any literature that uses CEM in an already randomized sample?
Thanks in advance,
Alisa
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