but when i'm running regressions with -micombine- and -mim-, i get different sample sizes. this shouldn't happen if i don't have missing data (which it seems i shouldn't have since i'm not using the first sample), right?
thanks for all your helpful answers!!!
----- Original Message ----
From: Maarten buis <[email protected]>
To: [email protected]
Sent: Wednesday, May 9, 2007 12:58:53 PM
Subject: Re: st: Missing data after multiple imputation
--- ucb_gal <[email protected]> wrote:
> Hi, I've run -ice- and my new imputed dataset still has missing data.
> Is this normal? If so, why does this happen?
Yes it is normal: -ice- stores the different datasets stacked on top of
each other. It differentiates between samples using the variable _mj.
The first sample (which is not used by -micombine- or -mim- has a value
for _mj of 0 and is just the original data, with missing values.
Hope this helps,
Maarten
-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting address:
Buitenveldertselaan 3 (Metropolitan), room Z434
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
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