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Re: st: RE: impute: too many variables specified

From   Michael Ingre <[email protected]>
To   [email protected]
Subject   Re: st: RE: impute: too many variables specified
Date   Fri, 19 Nov 2004 13:27:08 +0100

On 2004-11-19, at 11.37, chris wallace wrote:

Quite possibly the imputation would be not much different if I used 15 rather
than 17 predictor variables; I will investigate using regress. But as all
these biochemical measures relate to the same biochemical pathway, I am not
clear how to select "the best" 15 out of 17.
You might want to try multiple imputation (MI) instead. MI has better statistical properties than "single" imputation because it recognises the uncertainty in the imputed values by making multiple imputations in multiple datasets. After imputation you have to run your analyses on each of the datasets and combine the result into a single estimate. MI has been made available in Stata by Patrick Royston's -mice- package (st0067) and routines for estimating models and combining results are available within the -mice- package as well as in a package by Li, Greenwood & Carlin (st0042).

. ssc install mice
. whelp mvis
. whelp micombine
. whelp misplit
. net install st0042.pkg
. whelp miset
. whelp mifit

Michael Ingre , PhD student & Research Associate
Department of Psychology, Stockholm University &
National Institute for Psychosocial Medicine IPM
Box 230, 171 77 Stockholm, Sweden

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