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

From   Chris Wallace <[email protected]>
To   [email protected]
Subject   Re: st: RE: impute: too many variables specified
Date   Fri, 19 Nov 2004 10:34:41 +0000

Nick Cox wrote:

This was asked a while back. I can't remember the answer but it should be in the archives.

Thanks (and to Richard Williams and Kit Baum) - I found the mail and now understand the problem.

A quite different comment is to ask how much better your imputation is based on 30+ predictors
rather than 30.
The situation is that I have 17 biochemical variables, each measured twice (call them A1, A2, ..., Q1, Q2). Each of these need to be transformed into Xsum=X1+X2 and Xdiff=abs(X1-X2) - these will then be used in a score test.

Sometimes the biological assays fail. And so my missing values problem is doubled by this transformation (if X1 is missing, but not X2, both Xsum and Xdiff will be missing). So I wanted to -impute- the missing values for each Xsum and Xdiff, conditional on all A1-Q2.

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.

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