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

[Dan MacNulty <macn0007@umn.edu>]

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...
>
> HTH,
> Maarten
>
> -----------------------------------------
> 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
>
> http://home.fsw.vu.nl/m.buis/
> -----------------------------------------
>
> --- 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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