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Multiple imputation implementation
Hello,
Thanks again for the fantastic package!
I've been experimenting with the multimp
option in cmest
, which is great to have built-in; however, I've noticed that the imputation is carried out using only the variables included in the mediation models, even if the data frame includes additional variables.
It would be great if the package allowed the imputation models to differ (i.e., include a larger set of potential variables) to the mediation models. In cases where the exposure is missing, it may be that variables the are non-confounders within the mediation models are still useful for imputation.
I tried passing my own predictorMatrix
as an additional argument to mice
within cmest
but this returned an error.
Thanks again.