Multilevel imputation using MICE

miceMultilevelExample.R

# load data
load("ex.Rdata")

###################################
# example only using mice package
###################################

library(mice)

imp <- mice(ex, maxit = 0)
mat <- imp$predictorMatrix
meth <- imp$meth

# adjust prediction matrix
mat["frace",] <- 0
mat[c("frace", "cedui", "clinci", "dghealth"), "pid"] <- 0
mat[c("frace"), "pid"] <- -2

# redefine methods
meth["clinci"] <- "pmm"
meth["cedui"] <- "pmm"
meth["frace"] <- "2lonly.pmm"
meth["dghealth"] <- "pmm"

# I get warning messages
imp1 <- mice(ex, m = 1 , predictorMatrix = mat ,
             imputationMethod = meth ,
             maxit = 2)
                           

# adding male as predictor for frace 
mat["frace", "male"] <- 1

# I get an error
imp2 <- mice(ex, m = 1 , predictorMatrix = mat ,
             imputationMethod = meth ,
             maxit = 2)

##########################
# using miceadds package
##########################

library(miceadds)

imp <- mice(ex, maxit = 0)
mat <- imp$predictorMatrix
meth <- imp$meth

# adjust prediction matrix
mat["frace",] <- 0
mat[c("frace", "cedui", "clinci", "dghealth"), "pid"] <- 0
mat[c("frace"), "pid"] <- 1
mat[c("cedui", "clinci", "dghealth"), "pid"] <- -2

# redefine methods
meth["clinci"] <- "2l.pmm"
meth["cedui"] <- "2l.pmm"
meth["frace"] <- "pmm"
meth["dghealth"] <- "2l.pmm"
meth

# no warning messages
imp3 <- mice(ex, m = 1 , predictorMatrix = mat ,
             imputationMethod = meth ,
             maxit = 2)