多重插补的池化结果，pool()函数错误，mice包

Question

I am new to multiple imputation. I followed tutorials that I found online and performed multiple imputations on my own data. Everything went well until the very last step when I need to pool results from different data sets with imputed values. R gave me the following error messages:

pool(rep1_mi)
Error: No tidy method for objects of class qr
In addition: Warning messages:
1: In get.dfcom(object, dfcom) : Infinite sample size assumed.
2: 'tidy.numeric' is deprecated.
See help("Deprecated") 
3: 'tidy.numeric' is deprecated.
See help("Deprecated") 
4: 'tidy.numeric' is deprecated.
See help("Deprecated") 
5: 'tidy.numeric' is deprecated.
See help("Deprecated") 
6: 'tidy.numeric' is deprecated.
See help("Deprecated") 
7: 'tidy.numeric' is deprecated.
See help("Deprecated") 

I didn't find any solution that works. Could anyone please help? Thanks.

Answer 1

This GitHub issue is related to your problem. You can work around it by using the pool.scalar() function.

Answer 2

Try to run your model directly on the output given by mice and not on the output given by complete function

library(psych)
# to create some missingness 
bfi[4,1] = NA_character_
bfi[6,2] = NA_character_
bfi[9,1] = NA_character_
bfi[7,2] = NA_character_
bfi[6,1] = NA_character_

# run mice
imput.bfi <- mice(bfi, m = 3)

# when "complete" function is used, "pool" function will not run
bfi.imp.dat=mice::complete(imput.bfi, action="long", inc = TRUE)
# run linear regression 
lm.bfi=with(bfi.imp.dat, lm(N1 ~ age))
# pool will not work here 
pool(lm.bfi)


# In this case the "pool" function will work properly
# run linear regression 
lm.bfi=with(imput.bfi, lm(N1 ~ age))
# pool results 
pool(lm.bfi)