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First of all thanks for this amazing package and associated documentation, I really learned so much about missing data!
I noticed that I get slightly different results when running imputations that use a random forest model depending the OS/platform. This is even when defining the same seed. I tested the following reprex with the same R (4.3.2) and mice package version (3.17.0) on two different platforms (Linux Ubuntu and MacOS) and I get two slightly different results:
# mice version 3.17.0
library(mice)
# impute data
imp <- mice(
data = nhanes,
m = 20,
method = "rf",
rfPackage = "ranger",
seed = 1234,
printFlag = FALSE
)
# make long
imp_long <- complete(imp, action = "long")
# show bmi average
mean(imp_long$bmi)
Output on Ubuntu 20.04.6: 26.5236
Output on MacOS 15.2: 26.4744
I suspect it may have to do with the RNG invoked by the downstream random forest package.
The text was updated successfully, but these errors were encountered:
First of all thanks for this amazing package and associated documentation, I really learned so much about missing data!
I noticed that I get slightly different results when running imputations that use a random forest model depending the OS/platform. This is even when defining the same seed. I tested the following reprex with the same R (4.3.2) and mice package version (3.17.0) on two different platforms (Linux Ubuntu and MacOS) and I get two slightly different results:
Output on Ubuntu 20.04.6:
26.5236
Output on MacOS 15.2:
26.4744
I suspect it may have to do with the RNG invoked by the downstream random forest package.
The text was updated successfully, but these errors were encountered: