| mixMItest {micd} | R Documentation |
Likelihood Ratio Test for (Conditional) Independence between Mixed Variables after Multiple Imputation
Description
A modified version of mixCItest, to be used within pcalg::skeleton,
pcalg::pc or pcalg::fci when multiply imputed data sets are available.
Usage
mixMItest(x, y, S = NULL, suffStat, moreOutput = FALSE)
Arguments
x, y, S |
(integer) position of variable X, Y and set of variables S,
respectively, in |
suffStat |
A list of |
moreOutput |
(only for mixed of discrete variables) If |
Details
See mixCItest for details on the assumptions of the
Conditional Gaussian likelihood ratio test. CGtestMI applies this test
to each data.frame in suffStat, then combines the results using
the rules in Meng & Rubin (1992).
Value
A p-value. If moreOutput=TRUE, the test statistic, its main
components and the degrees of freedom are returned as well.
Author(s)
Janine Witte
References
Meng X.-L., Rubin D.B. (1992): Performing likelihood ratio tests with multiply imputed data sets. Biometrika 79(1):103-111.
Examples
## 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
pc.fit <- pc(suffStat = suffMI, indepTest = mixMItest, alpha = 0.01, p = 5)
pc.fit