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Re: st: Issue with multiple imputation -ICE-


From   Mark Lunt <Mark.Lunt@manchester.ac.uk>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Issue with multiple imputation -ICE-
Date   Wed, 13 Feb 2008 17:20:41 +0000

René Wevers wrote:
Dear Statalisters,

I am working with an extensive dataset (10.000+ observations) and
logically some values are missing. I decided to use the -ice- package to
impute certain missing values, but the result simply makes no sense to me.

For instance I am estimating missing variables for the full time
equivalent (FTE) of employees of a company mainly based on the absolute
number of employees. (Logically) the absolute number of employees is never
below zero. Also when I run a regression between the FTE number and
absolute number I get a highly significant relation with positive
coefficient and a positive constant estimates. Nevertheless when I run
-ice-, the imputed values are extremely often (far) below zero (!!!). Also
worrying is that the imputed values are practically all completely
different (over factor 100) from the absolute number of employees, where a
closer relation is (logically) expected.

Is there some explanation for this or are we making any mistakes.

ICE assumes that continuous variables are normally distributed: if that is not the case, impossible values can appear. In particular, if you have lots of companies with a few employees and a few companies with lots of employees, ICE will impute negative numbers of employees. One possible solution is to use the "match" option of ICE. Alternatively, I have written some ado-files which convert variables to normal-scores and back: you can convert to normal scores (which are normally distributed), perform the imputation on these variables, then convert back to your original distribution. If you are interested in using these ado-files, type

net from http://personalpages.manchester.ac.uk/staff/mark.lunt

into stata, then click on the blue "nscores"

Hope that's of some use

Mark

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