## load data (numeric and factor variables)
library(ranger)
dat <- toenail2[1:400, ]
## delete some observations
set.seed(123)
dat[sample(400, 20), 2] <- NA
dat[sample(400, 30), 4] <- NA
## impute missing values using random forests
imp <- mice::mice(dat, method = "rf", m = 3, printFlag = FALSE)
## obtain correct input 'suffStat' for 'flexMItest'
suff <- getSuff(imp, test="flexMItest")
## analyse data
# continuous variables only
flexMItest(4,5,NULL, suffStat = suff)
implist <- complete(imp, action="all")
gaussSuff <- c(lapply(implist, function(i){cor(i[ ,c(4,5)])}), n = 400)
gaussMItest(1,2,NULL, suffStat = gaussSuff)
flexCItwd(4, 5, NULL, dat)
# discrete variables only
flexMItest(2,3,NULL, suffStat = suff)
disMItest(2,3,NULL, suffStat = complete(imp, action="all"))
flexCItwd(2,3,NULL, dat)
# mixed variables
flexMItest(2,3,4, suffStat = suff)
mixMItest(2,3,4, suffStat = complete(imp, action="all"))
flexCItwd(2,3,4, dat)
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