OK, thanks.... any suggestions in the meantime?
I can use SAS, but I don't like their imputation methods in this case.
Or maybe I can just look at the five outputs, and see if any were much different from the
results with casewise deletion?
Thanks
Peter
-----Original Message-----
From: Kosuke Imai <kimai(a)Princeton.Edu>
Sent: Jan 18, 2010 3:13 PM
To: Peter Flom <peterflomconsulting(a)mindspring.com>
Cc: zelig(a)lists.gking.harvard.edu
Subject: Re: [zelig] summary with imputations bug ... any workarounds?
Unfortunately, mixed effects models are not currently compartible with
multiply imputed data sets. It's on our to-do list...
Kosuke
--
Department of Politics
Princeton University
http://imai.princeton.edu
On Fri, 15 Jan 2010, Peter Flom wrote:
Good morning
If I run
<<<
susan.lsmixed.out <- zelig(formula = unprot_vag_sex ~ married + age +
TREATMENT.ARM*time + highest_grade + income + tag(1|id),
data = susanMI.out$imputations, model = "ls.mixed")
summary(susan.lsmixed.out)
>>>
I get an error
Error in x$coef : $ operator is invalid for atomic vectors
Searching the archives, I see that others have had similar problems. Is there a
workaround?
summary(susan.lsmixed.out[[1]])
works fine; should I then average across the five imputed data sets?
thanks!
Peter
Peter L. Flom, PhD
Statistical Consultant
Website:
http://www DOT statisticalanalysisconsulting DOT com/
Writing;
http://www.associatedcontent.com/user/582880/peter_flom.html
Twitter: @peterflom
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