complete.mids {mice} | R Documentation |
Extracts the completed data from a mids
object
Description
Takes an object of class mids
, fills in the missing data, and returns
the completed data in a specified format.
Usage
## S3 method for class 'mids'
complete(data, action = 1L, include = FALSE, mild = FALSE, ...)
Arguments
data |
An object of class |
action |
A numeric vector or a keyword. Numeric
values between 1 and |
include |
A logical to indicate whether the original data with the missing values should be included. |
mild |
A logical indicating whether the return value should
always be an object of class |
... |
Additional arguments. Not used. |
Details
The argument action
can be length-1 character, which is
matched to one of the following keywords:
"all"
produces a
mild
object of imputed data sets. Wheninclude = TRUE
, then the original data are appended as the first list element;"long"
produces a data set where imputed data sets are stacked vertically. The columns are added: 1)
.imp
, integer, referring the imputation number, and 2).id
, character, the row names ofdata$data
;"stacked"
same as
"long"
but without the two additional columns;"broad"
produces a data set with where imputed data sets are stacked horizontally. Columns are ordered as in the original data. The imputation number is appended to each column name;
"repeated"
same as
"broad"
, but with columns in a different order.
Value
Complete data set with missing values replaced by imputations.
A data.frame
, or a list of data frames of class mild
.
Note
Technical note: mice 3.7.5
renamed the complete()
function
to complete.mids()
and exported it as an S3 method of the
generic tidyr::complete()
. Name clashes between
mice::complete()
and tidyr::complete()
should no
longer occur.
See Also
Examples
# obtain first imputed data set
sum(is.na(nhanes2))
imp <- mice(nhanes2, print = FALSE, maxit = 1)
dat <- complete(imp)
sum(is.na(dat))
# obtain stacked third and fifth imputation
dat <- complete(imp, c(3, 5))
# obtain all datasets, with additional identifiers
head(complete(imp, "long"))
# same, but now as list, mild object
dslist <- complete(imp, "all")
length(dslist)
# same, but also include the original data
dslist <- complete(imp, "all", include = TRUE)
length(dslist)
# select original + 3 + 5, store as mild
dslist <- complete(imp, c(0, 3, 5), mild = TRUE)
names(dslist)