[R] multiple imputation with fit.mult.impute in Hmisc
Frank E Harrell Jr
fharrell at virginia.edu
Mon Jul 28 04:20:10 CEST 2003
On Sun, 27 Jul 2003 14:47:30 -0400
Jonathan Baron <baron at psych.upenn.edu> wrote:
> I have always avoided missing data by keeping my distance from
> the real world. But I have a student who is doing a study of
> real patients. We're trying to test regression models using
> multiple imputation. We did the following (roughly):
>
> f <- aregImpute(~ [list of 32 variables, separated by + signs],
> n.impute=20, defaultLinear=T, data=t1)
> # I read that 20 is better than the default of 5.
> # defaultLinear makes sense for our data.
>
> fmp <- fit.mult.impute(Y ~ X1 + X2 ... [for the model of interest],
> xtrans=f, fitter=lm, data=t1)
>
> and all goes well (usually) except that we get the following
> message at the end of the last step:
>
> Warning message: Not using a Design fitting function;
> summary(fit) will use standard errors, t, P from last imputation
> only. Use Varcov(fit) to get the correct covariance matrix,
> sqrt(diag(Varcov(fit))) to get s.e.
>
> I did try using sqrt(diag(Varcov(fmp))), as it suggested, and it
> didn't seem to change anything from when I did summary(fmp).
>
> But this Warning message sounds scary. It sounds like the whole
> process of multiple imputation is being ignored, if only the last
> one is being used.
The warning message may be ignored. But the advice to use Varcov(fmp) is faulty for lm fits - I will fix that in the next release of Hmisc. You may get the imputation-corrected covariance matrix for now using fmp$var
>
> So I discovered I could get rid of this warning by loading the
> Design library and then using ols instead of lm as the fitter in
> fit.mult.imput. It seems that ols provides a variance/covariance
> matrix (or something) that fit.mult.impute can use.
That works too.
Frank
>
> But here I am beyond my (very recently acquired) understanding of
> what this is all about.
>
> Should I worry about that warning message? Or am I maybe off the
> track in some larger way?
>
> --
> Jonathan Baron, Professor of Psychology, University of Pennsylvania
> Home page: http://www.sas.upenn.edu/~baron
> R page: http://finzi.psych.upenn.edu/
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
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---
Frank E Harrell Jr Prof. of Biostatistics & Statistics
Div. of Biostatistics & Epidem. Dept. of Health Evaluation Sciences
U. Virginia School of Medicine http://hesweb1.med.virginia.edu/biostat
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