mice (version 2.30)

complete: Creates imputed data sets 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

complete(x, action = 1, include = FALSE)

Arguments

x

An object of class mids as created by the function mice().

action

If action is a scalar between 1 and x$m, the function returns the data with imputation number action filled in. Thus, action=1 returns the first completed data set, action=2 returns the second completed data set, and so on. The value of action can also be one of the following strings: 'long', 'broad', 'repeated'. See 'Details' for the interpretation.

include

Flag to indicate whether the orginal data with the missing values should be included. This requires that action is specified as 'long', 'broad' or 'repeated'.

Value

A data frame with the imputed values filled in. Optionally, the original data are appended.

Details

The argument action can also be a string, which is partially matched as follows:

list('\'long\'')

produces a long data frame of vertically stacked imputed data sets with nrow(x$data) * x$m rows and ncol(x$data)+2 columns. The two additional columns are labeled .id containing the row names of x$data, and .imp containing the imputation number. If include=TRUE then nrow(x$data) additional rows with the original data are appended with .imp set equal to 0.

list('\'broad\'')

produces a broad data frame with nrow(x$data) rows and ncol(x$data) * x$m columns. Columns are ordered such that the first ncol(x$data) columns corresponds to the first imputed data matrix. The imputation number is appended to each column name. If include=TRUE then ncol(x$data) additional columns with the original data are appended. The number .0 is appended to the column names.

list('\'repeated\'')

produces a broad data frame with nrow(x$data) rows and ncol(x$data) * x$m columns. Columns are ordered such that the first x$m columns correspond to the x$m imputed versions of the first column in x$data. The imputation number is appended to each column name. If include=TRUE then ncol(x$data) additional columns with the original data are appended. The number .0 is appended to the column names.

See Also

mice, mids

Examples

# NOT RUN {

# do default multiple imputation on a numeric matrix
imp <- mice(nhanes)

# obtain first imputated matrix
mat <- complete(imp)

# fill in the third imputation
mat <- complete(imp, 3)

# long matrix with stacked complete data
mat <- complete(imp, 'long')

# long matrix with stacked complete data, including the original data
mat <- complete(imp, 'long', inc=TRUE)

# repeated matrix with complete data
mat <- complete(imp, 'r')

# for numeric data, produces a blocked correlation matrix, where
# each block contains of the same variable pair over different
# multiple imputations.
cor(mat)

# }