miceadds (version 1.5-0)

write.mice.imputation: Export Multiply Imputed Datasets from a mids Object

Description

Exports multiply imputed datasets and information about the imputation. Objects of class mids (generated by mice::mice) and mids.1chain (generated by mice.1chain) are supported.

Usage

write.mice.imputation(mi.res, name, include.varnames = TRUE,
      long = TRUE, mids2spss = TRUE, spss.dec = ",", dattype = NULL)

Arguments

mi.res

Object of class mids or mids.1chain

name

Name of created folder and datasets

include.varnames

An optional logical indicating whether variable names should be included in the imputed dataset. The default is TRUE.

long

An optional logical indicating whether the dataset should also be saved in a long format?

mids2spss

An optional logical indicating whether a syntax for reading imputed datasets in SPSS should be included

spss.dec

SPSS decimal separator (can be "," or ".")

dattype

Format of the saved dataset: csv or csv2

Value

• Several files are saved using impxxx (the name) as the prefix:
• impxxx.Rdata
  Saved object of class mids
• impxxx__DATALIST.Rdata
  Saved object of a list containing multiply imputed datasets
• impxxx__IMP_LIST
  File with list of multiply imputed datasets
• impxxx__IMP_SUMMARY
  Summary file of the imputation
• impxxx__IMPDATA_nn
  Imputed datasets nn
• impxxx__IMPMETHOD
  File containing imputation methods
• impxxx__LEGENDE
  File with variable names of the dataset
• impxxx__LONG
  Imputed datasets in long format
• impxxx__PREDICTORMATRIX
  File containing the predictor matrix
• impxxx__SPSS.sps
  SPSS syntax for reading the corresponding txt file into SPSS format.

See Also

See also mice::mids2mplus and mice::mids2spss

Examples

#############################################################################
# EXAMPLE 1: Imputation of nhanes data and write imputed datasets on disk
#############################################################################

data(nhanes,package="mice")

#**********
# Model 1: Imputation using mice
imp1 <- mice( nhanes , m=3 , maxit=5 )
# write results
write.mice.imputation(mi.res=imp1 , name="mice_imp1" )

#**********
# Model 2: Imputation using mice.1chain
imp2 <- mice.1chain( nhanes , burnin=10 , iter=20 , Nimp=4 )
# write results
write.mice.imputation(mi.res=imp2 , name="mice_imp2" )