## load data (numeric and factor variables)
data(toenail2)
dat <- toenail2[1:1000, ]
## delete some observations
set.seed(123)
dat[sample(1000, 20), 2] <- NA
dat[sample(1000, 30), 4] <- NA
## impute missing values using random forests (because of run time we just impute 2 chains)
imp <- mice(dat, method = "rf", m = 2, printFlag = FALSE)
## analyse data
# complete data:
mixCItest(2, 3, 5, suffStat = toenail2[1:1000, ])
# multiple imputation:
suffMI <- complete(imp, action = "all")
mixMItest(2, 3, 5, suffStat = suffMI)
# test-wise deletion:
mixCItwd(2, 3, 5, suffStat = dat)
# list-wise deletion:
sufflwd <- dat[complete.cases(dat), ]
mixCItest(2, 3, 5, suffStat = sufflwd)
## use mixMItest within pcalg::pc
# \donttest{
pc.fit <- pc(suffStat = suffMI, indepTest = mixMItest, alpha = 0.01, p = 5)
pc.fit
# }
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