| subset_datlist {miceadds} | R Documentation |
Subsetting Multiply Imputed Datasets and Nested Multiply Imputed Datasets
Description
Returns a subsets of multiply imputed datasets or nested multiply imputed datasets.
These function allows choosing parts of the imputed datasets using the
index argument for multiply imputed datasets and index_between and
index_within for nested multiply imputed datasets as well as the application
of the base::subset S3 method for selecting
cases and variables in datasets.
Usage
subset_datlist(datlist, subset=TRUE, select=NULL, expr_subset=NULL,
index=NULL, toclass="datlist")
## S3 method for class 'datlist'
subset(x, subset, select=NULL, expr_subset=NULL,
index=NULL, ...)
## S3 method for class 'imputationList'
subset(x, subset, select=NULL, expr_subset=NULL,
index=NULL, ...)
## S3 method for class 'mids'
subset(x, subset, select=NULL, expr_subset=NULL,
index=NULL, ...)
## S3 method for class 'mids.1chain'
subset(x, subset, select=NULL, expr_subset=NULL,
index=NULL, ...)
subset_nested.datlist( datlist, subset=TRUE, select=NULL, expr_subset=NULL,
index_between=NULL, index_within=NULL, toclass="nested.datlist",
simplify=FALSE )
## S3 method for class 'nested.datlist'
subset(x, subset, select=NULL, expr_subset=NULL,
index_between=NULL, index_within=NULL, simplify=FALSE, ...)
## S3 method for class 'NestedImputationList'
subset(x, subset, select=NULL, expr_subset=NULL,
index_between=NULL, index_within=NULL, simplify=FALSE, ...)
Arguments
datlist |
For |
subset |
Logical expression indicating elements or rows to keep, see
|
select |
Expression indicating columns to select from a data frame |
expr_subset |
Expression indicating a selection criterion for selection rows. |
index |
Vector of indices indicating which of the multiply imputed datasets should be selected. |
toclass |
The object class in which the datasets should be saved. |
index_between |
Index for between nest datasets |
index_within |
Index for within nest datasets |
simplify |
Optional logical indicating whether a nested multiply imputed dataset should be simplified to a multiplied imputed dataset. |
x |
Object containing multiply imputed or nested multiply imputed datasets |
... |
Further arguments to be passed. |
Value
For multiply imputed datasets: Object of class datlist,
imputationList or mids
For nested multiply imputed datasets: Object of class
nested.datlist or NestedImputationList.
Note
If subsetting is applied to objects of class mids (or mids.1chain),
then informations about the imputation procedure are lost.
See Also
Examples
## Not run:
#############################################################################
# EXAMPLE 1: Subsetting and selection of multiply imputed datasets
#############################################################################
data(data.ma02)
# define original list of datasets
datlist1a <- data.ma02
# object of class datlist
datlist1b <- miceadds::datlist_create(datlist1a)
datlist1b
# object of class imputationList
datlist1c <- mitools::imputationList(datlist1a)
datlist1c
# object of class mids
datlist1d <- miceadds::datlist2mids(datlist1a)
datlist1d
# select some imputed datasets
datlist2a <- miceadds::subset_datlist( datlist1a, index=c(5,3,7) )
datlist2a
# convert to class imputationList
datlist2b <- miceadds::subset_datlist( datlist1a, index=c(5,3,7),
toclass="imputationList")
datlist2b
# convert to class mids
datlist2c <- miceadds::subset_datlist( datlist1a, index=1:3, toclass="mids")
datlist2c
# select some variables
datlist3a <- miceadds::subset_datlist( datlist1a, select=c("idstud", "books") )
datlist3a
# Because datlist1b is a datlist it is equivalent to
datlist3b <- subset( datlist1b, select=c("idstud", "books") )
datlist3b
# operating on imputationList class
datlist3c <- miceadds::subset_datlist( datlist1c, select=c("idstud", "books") )
datlist3c
# operating on mids class
datlist3d <- miceadds::subset_datlist( datlist1d, select=c("idstud", "books") )
datlist3d
# selection of rows and columns in multiply imputed datasets
datlist4a <- miceadds::subset_datlist( datlist1a, index=1:5,
subset=datlist1a[[1]]$idschool < 1067,
select=c("idstud", "idschool","hisei") )
datlist4a
# convert to class mids
datlist4b <- miceadds::subset_datlist( datlist1a, index=1:5,
subset=datlist1a[[1]]$idschool < 1067,
select=c("idstud", "idschool","hisei"), toclass="mids" )
datlist4b
# The same functionality, but now applying to object of class mids datlist1d
datlist4c <- miceadds::subset_datlist( datlist1d, index=1:5,
subset=datlist1a[[1]]$idschool < 1067,
select=c("idstud", "idschool","hisei") )
datlist4c
# expression for selecting rows specific in each data frame
# which can result in differently sized datasets (because the variable
# migrant is imputed)
datlist5a <- miceadds::subset_datlist( datlist1a, expr_subset=expression(migrant==1) )
datlist5a
# select the first 100 cases
datlist6a <- miceadds::subset_datlist( datlist1a, select=c("idstud", "books"),
subset=1:100 )
datlist6a
#############################################################################
# EXAMPLE 2: Subsetting and selection of nested multiply imputed datasets
#############################################################################
library(BIFIEsurvey)
data(data.timss4, package="BIFIEsurvey")
dat <- data.timss4
# create object of class 'nested.datlist'
datlist1a <- miceadds::nested.datlist_create( dat )
# create object of class 'NestedImputationList'
datlist1b <- miceadds::NestedImputationList(dat)
# select some between datasets
datlist2a <- subset_nested.datlist( datlist1a, index_between=c(1,3,4) )
datlist2a
# shorter version
datlist2b <- subset( datlist1a, index_between=c(1,3,4) )
datlist2b
# conversion of a NestedImputationList
datlist2c <- subset( datlist1b, index_between=c(1,3,4))
datlist2c
# select rows and columns
sel_cases <- datlist1a[[1]][[1]]$JKZONE <=42
datlist3a <- subset( datlist1a, subset=sel_cases,
select=c("IDSTUD","books", "ASMMAT") )
datlist3a
# remove within nest
datlist4a <- subset( datlist1a, index_within=1 )
datlist4a
# remove within nest and simplify structure
datlist4b <- subset( datlist1a, index_within=1, simplify=TRUE)
datlist4b
datlist4c <- subset( datlist1b, index_within=1, simplify=TRUE)
datlist4c
# remove between nest
datlist5a <- subset( datlist1a, index_between=1, simplify=TRUE)
datlist5a
datlist5b <- subset( datlist1b, index_between=1, simplify=TRUE)
datlist5b
## End(Not run)