RMS Discussions

[R_cubed]

RE: Multiple Imputation with Bootstrap.

There was a thread on this a few months ago with some good references in the comments.

Bootstrapping CIs in multiply imputed data

Background: I plan to estimate the average causal effect of a continuous exposure on my outcome using the parametric g-formula (i.e., standardized mean difference), and I need to bootstrap the 95% CIs. I’d like to use 1000 (or some other sufficiently large number of) bootstrap samples, if possible. I also have missing data in my confounders and will impute it via MICE. I’m reasonably confident in my imputation models. Despite only a moderate degree of missingness, I’d like to create something o…

In a different forum, a practicing statistician indicated to me that bootstrapping, then imputation was generally best. There do exist times when it is possible to get comparable results (with less computational cost) doing imputation first, then bootstrapping, but care needs to be exercised to make sure the variance is not an under-estimate.