Making sure something is kosher

I think you mean to ask, how does one pool bootstrapped confidence
intervals constructed from 20 imputations? Same question about variance
estimates, or ICC. Appears now, each of those is a separate battle.
Similarly, any anova() test done separately. Rubin's rules great for MLEs.
Not so much for all that other stuff that we do.

VanBuren worked out the R^2 and some papers exist on model chisquare.
if you find one on CI, let me know. I'm wondering if you could simply
aggregate runs and build a CI. if not, appears you need better math stat
training than I have.

One project here explored that. If you are in the "I need 100 imputations"
crew and you want 5000 bootstraps, well... get a cluster. I'll ask that
team what they know.

pj
Paul Johnson
http://pj.freefaculty.org

I realize combining multiple imputation with random effect estimation is
dodgy.

Supposing I use mice with glmer to do the model fits, and then bootstrap to
get confidence intervals on the random effect estimates.

Is that a clean way to do it?  If not, what's recommended?

Thanks!



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