[R] mice package

[Bert Gunter]

While your queries certainly intersect R , they are mostly about
statistical methodology for this special kind of missing data. This list is
mostly about R programming. I think you would do better posting to a
statistics list, like stats.stackexchange.com . Advice there might bring
you back here to ask about R implementation, but that's not your current
concern.

Cheers,

Bert

On Monday, March 7, 2016, Giuseppe Biondi Zoccai <gbiondizoccai at gmail.com>
wrote:

> I am using the mice package to impute some missing values, and it work
> nicely.
> I am facing a tricky strategic question though.
> Basically, I am working on predictors of myocardial infarction, with all
> patients having baseline features (eg age, gender), despite a few missing
> values.
> Some patients have performed also a stress test, with specific continous
> details (eg stress duration), but others haven't.
> What should I do to capture the information associated with stress test
> features?
> A complete case analysis will of course exclude all those without a stress
> test (roughly 50%).
> Is it reasonable to impute with mice the stress features among also those
> who did not undergo any stress test?
> Or should I best create a factor variable such as stress_status (0- no
> stress, 1-stress with low tolerance, 2-stress with high tolerance, and so
> forth)?
> Thanks for the help
> Giuseppe
>
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>
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-- 
Bert Gunter

"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )

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