complete {mice}R Documentation

Creates a Complete Flat File from a Multiply Imputed Data Set

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)

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 the action's imputation 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.

Details

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

"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.
"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.
"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.

Value

A data frame with the imputed values filled in.

Author(s)

Stef van Buuren, Karin Groothuis-Oudshoorn, 2000

See Also

mice, mids

Examples

data(nhanes)

# 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") 

# 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)               

[Package mice version 1.21 Index]