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Re: st: Issues of Normality for Multiple Imputation with ICE


From   Fred Wolfe <fwolfe@arthritis-research.org>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Issues of Normality for Multiple Imputation with ICE
Date   Fri, 9 Oct 2009 09:56:26 -0500

You can use the -boot- option in -ice-. The help file says: "    With
the boot option, steps 2-4 are replaced by a bootstrap estimation of
beta_star and sigma_star, obtained by regressing yvar on xvars after
taking a bootstrap sample of the non-missing observations. This has
the  advantage of robustness since the distribution of beta is no
longer assumed to be multivariate normal."

Fred


On Fri, Oct 9, 2009 at 9:48 AM, McDonald, Catherine
<mcdonalc@nursing.upenn.edu> wrote:
>
> Hello-
>
> I am working with a small data set with missing values for which I am trying to do multiple imputation with ICE. I have some data that are non-normal. Do I have to do transformations? I have seen a reference to Schafer (Analysis of incomplete Multivariate Data 1997) that says there is evidence that imputation methods can work even when the data are not normal. But I did not know if the ICE command would be one of these methods. Is there a ref that would support leaving non-normal data as is for multiple imputation with ICE? Are there steps that I need to take? What options for transformations would be possible?
>
> Thank you very much-
> Catherine
>
>
>
>
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--
Fred Wolfe
National Data Bank for Rheumatic Diseases
Wichita, Kansas
NDB Office  +1 316 263 2125 Ext 0
Research Office +1 316 686 9195
fwolfe@arthritis-research.org

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