Export Multiply Imputed Datasets from a mids Object
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.
write.mice.imputation(mi.res, name, include.varnames=TRUE, long=TRUE, mids2spss=TRUE, spss.dec=",", dattype=NULL)
mi.res |
Object of class |
name |
Name of created subdirectory and datasets |
include.varnames |
An optional logical indicating whether variable names should be included
in the imputed dataset. The default is |
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 |
dattype |
Format of the saved dataset: |
Several files are saved using impxxx
(the name
)
as the prefix:
impxxx.Rdata |
Saved object of class |
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 |
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
|
See also mice::mids2mplus
and
mice::mids2spss
## Not run: ############################################################################# # EXAMPLE 1: Imputation of nhanes data and write imputed datasets on disk ############################################################################# data(nhanes,package="mice") #********** # Model 1: Imputation using mice imp1 <- mice::mice( nhanes, m=3, maxit=5 ) # write results write.mice.imputation(mi.res=imp1, name="mice_imp1" ) #********** # Model 2: Imputation using mice.1chain imp2 <- miceadds::mice.1chain( nhanes, burnin=10, iter=20, Nimp=4 ) # write results write.mice.imputation(mi.res=imp2, name="mice_imp2" ) ## End(Not run)
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