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Re: st: RE: Re: subject-specific imputation with ICE

From   Dan MacNulty <>
Subject   Re: st: RE: Re: subject-specific imputation with ICE
Date   Sun, 15 Oct 2006 14:17:30 -0700

Maarten - Thanks for the helpful reply.

Dan MacNulty

Maarten Buis wrote:
Dan and Sarah:
I have dealt with a similar problem only in my case individuals were nested within surveys. I ran -ice- separately for each survey and combined the imputed files afterwards. Because I wanted to include interaction with each annual dummy and gender, I actually rand -ice- separately for each survey, year, gender combination.
One thing to keep in mind is to make sure you have more completely observed cases than variables in your imputation model for each call to -ice-. -ice- will not complain if you don't, but it won't converge, and it won't tell you that it hasn't converged, since convergence is a tricky issue with -ice- (you can run -ice- with the trace option and lots of cycles and look at a lineplot of mean imputed value versus cycle, and the result should show no trend if it converged). In my case, before I found out what was going on, the results were really of. It took me a while to find out what was going on, especially since I first estimated the model using interactions with all the dummies. Not enough observations isn't the first thing you think about if you have a 100,000+ observations...


Maarten L. Buis
Department of Social Research Methodology Vrije Universiteit Amsterdam Boelelaan 1081 1081 HV Amsterdam The Netherlands

visiting adress:
Buitenveldertselaan 3 (Metropolitan), room Z434
+31 20 5986715

--- Sarah A. Mustillo wrote:

I was waiting for someone else to reply, but haven't seen any cross
the list.  When I use ICE, I impute within each subject.  I have no
citations on this or anything to support that approach, it just
intuitively seemed to me that it could be problematic to impute across
the entire dataset when the obs are correlated.  So, I reshape the data
to wide and impute as one observation per person.  Whether this actually
makes a difference is probably questionable.  At some point I'll try it
both ways and compare...

Dan MacNulty wrote:

I have two questions with respect to imputation and the program ICE. In
situations where data are subject-specific, e.g. clustered within
patient_ID, is it recommended that one impute within each subject or is
it sufficient to impute across the entire dataset? If the former, can
ICE be implemented to impute missing values within each subject, and if
so, how?

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