mitml.list to midsmitml.list2mids.RdThis function converts a mitml.list class object to mids (as used in the mice package).
mitml.list2mids(x, data, fill = FALSE, where = NULL)A list of imputed data sets with class mitml.list (as produced by mitmlComplete, mids2mitml.list, or similar).
A data frame containing to original (incomplete) data (see 'Details').
A logical flag indicating whether variables in the imputed data that are not in the original data should be added and filled with NA (default is FALSE).
(optional) A data frame or matrix of logicals indicating the location of missing values (see 'Details').
This function converts objects of class mitml.list into mids objects (as used in the mice package).
The conversion requires a list of imputed data sets and the original (incomplete) data set.
If the imputed data sets have been appended with new variables (e.g., by within.mitml.list), the new variables can be added to the original data set by setting fill = TRUE.
This function is essentially a wrapper around as.mids that sets the case and imputation identifiers automatically and and passes the where argument as is (see also the documentation of as.mids).
An object of class mids.
data(studentratings)
fml <- ReadDis + SES ~ ReadAchiev + (1|ID)
imp <- panImpute(studentratings, formula = fml, n.burn = 1000, n.iter = 100, m = 5)
#> Running burn-in phase ...
#> Creating imputed data set ( 1 / 5 ) ...
#> Creating imputed data set ( 2 / 5 ) ...
#> Creating imputed data set ( 3 / 5 ) ...
#> Creating imputed data set ( 4 / 5 ) ...
#> Creating imputed data set ( 5 / 5 ) ...
#> Done!
implist <- mitmlComplete(imp)
# * Example 1: simple conversion
# convert to 'mids'
impmids <- mitml.list2mids(implist, data = studentratings)
# * Example 2: conversion with additional variables
# compute new variables
implist <- within(implist, {
M.ReadAchiev <- clusterMeans(ReadAchiev, ID)
C.ReadAchiev <- ReadAchiev - M.ReadAchiev
})
# convert to 'mids'
impmids <- mitml.list2mids(implist, data = studentratings, fill = TRUE)