

Hi to
everyone, I have a big data set where rows are observations and columns are
variables. It contains a lot of missing values. I have used multiple imputation
with library mice and I get an “exact” prediction of each missing value. Now, I
would like to know the error I can commit or the confidence interval.

How can I
get this?

This is
part of my code

library(mice)

mod1<-mice(dat,
method=c("","",rep("pmm",6)))

                ro<-round(cor(dat,
use = "pair"), 3)

 

                predictor<-quickpred(dat)#
esta matriz predictora se construye según las correlaciones

                

                mod1<-mice(dat,method=c("","",rep("pmm",6)),
pred=predictor)

                imputados<-complete(mod1,'long')

                x.imp=split(imputados,
imputados$.imp)

                acumula=x.imp[[1]][,-c(1,2)]

                                               for(j
in 2:length(x.imp))

                                                               {
acumula=acumula+x.imp[[j]][,-c(1,2)]}

                med.imp=acumula/5

 

 

Thanks in
advance 		 	   		   		 	   		  
	[[alternative HTML version deleted]]

