Quoting Michael Ingre <[email protected]>:
>
> 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.
Thank you. One reason I'd rather not resort to MI is that I already need to use
permutation to determine p-values, and doing this for multiply imputed datasets
would be time consuming. Also I am planning to use a score test, and my
understanding is that score tests of null hypotheses are unbiased even when the
uncertainty in the singly imputed values is ignored. I don't recall the
reference for this though - perhaps I've misunderstood?
Chris.
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