Hello,
I am looking into using CEM in a context where I need to match subsets of
the treatment group separately based on the timing of treatment
(unfortunately, the simple solution of using time as a matching component
won't work in my case).
After matching, I would like to combine the matched subsets to estimate a
pooled treatment effect. Do the cem_weights need to be revised to account
for pooling? If so, is there a reference that describes how the cem_weights
are created? I understand their basic purpose - to account for differential
strata sizes - but I'm not clear on the actual formula that is used to
generate the weights for matched controls.
Thank you,
Zack
Hi Catherine, thanks for your note to the list. It sounds like you could
define this as at one level but with multiple (rather than binary)
treatment regimes. Our papers on cem explain how that works. Best of luck
with your research. Gary King
---
GaryKing.org
617-500-7570
On Dec 2, 2016 4:49 PM, "Catherine E Hendrick" <emily.hendrick(a)utexas.edu>
wrote:
I am considering using Coarsened Exact Matching in order to study the
effects of teen mothers' degree type (GED v. HS diploma) on long-term
outcomes. In order to sufficiently address my research questions, it seems
that I may need two levels of matching:
1) matching those who attained a GED with those who attained a HS diploma
(to isolate the effects of degree type on outcomes)
2) matching teen mothers with women who began childbearing after the
teenage years (to determine if diploma type effects on later outcomes are
the same or different for women who began childbearing during the teenage
years v. later)
I haven't seen any literature using CEM that conducts two levels of
matching as I am proposing. Do you know of literature where researchers
have done this and/or do you see any methodological reason for NOT
conducting two levels of matching, as I have proposed, when using CEM?
Many thanks for any information you're able to pass along.
