I'm running MICE for 100 imputations with big data (~600k rows). Due to storage restrictions at work (which I am not permitted to change), I can't save all 100 imputations in one go, and I'd hit memory issues in R anyway.

I am thinking of running mice with 1 imputation (m = 1), then saving that imputation to Excel, deleting the imputation in R, and repeating this 100 times. This will only work if running the MICE command 100 separate times with m = 1 is functionally equivalent to running it once with m = 100.

I trialled this by running MICE with m = 2 and then twice with m = 1, and the outputs were different, which is what I was hoping for. However, it would be useful if I could find this information for certain.


1 Answer 1


You can change the seed argument in each iteration of your mice call to ensure a different imputation.


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