cbind.mids: Combine 'mids' objects by columns

Description Usage Arguments Details Value Note Author(s) See Also Examples

View source: R/cbind.R

Description

This function combines two mids objects columnwise into a single object of class mids, or combines a single mids object with a vector, matrix, factor or data.frame columnwise into a mids object.

Usage

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cbind.mids(x, y = NULL, ...)

Arguments

x

A mids object.

y

A mids object, or a data.frame, matrix, factor or vector.

...

Additional data.frame, matrix, vector or factor. These can be given as named arguments.

Details

Pre-requisites: If y is a mids-object, the rows of x$data and y$data should match, as well as the number of imputations (m). Other y are transformed into a data.frame whose rows should match with x$data.

The function renames any duplicated variable or block names by appending ".1", ".2" to duplicated names.

Value

An S3 object of class mids

Note

The function constructs the elements of the new mids object as follows:

data Columnwise combination of the data in x and y
imp Combines the imputed values from x and y
m Taken from x$m
where Columnwise combination of x$where and y$where
blocks Combines x$blocks and y$blocks
call Vector, call[1] creates x, call[2] is call to cbind.mids
nmis Equals c(x$nmis, y$nmis)
method Combines x$method and y$method
predictorMatrix Combination with zeroes on the off-diagonal blocks
visitSequence Combined as c(x$visitSequence, y$visitSequence)
formulas Combined as c(x$formulas, y$formulas)
post Combined as c(x$post, y$post)
blots Combined as c(x$blots, y$blots)
ignore Taken from x$ignore
seed Taken from x$seed
iteration Taken from x$iteration
lastSeedValue Taken from x$lastSeedValue
chainMean Combined from x$chainMean and y$chainMean
chainVar Combined from x$chainVar and y$chainVar
loggedEvents Taken from x$loggedEvents
version Current package version
date Current date

Author(s)

Karin Groothuis-Oudshoorn, Stef van Buuren

See Also

cbind, rbind.mids, ibind, mids

Examples

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# impute four variables at once (default)
imp <- mice(nhanes, m = 1, maxit = 1, print = FALSE)
imp$predictorMatrix

# impute two by two
data1 <- nhanes[, c("age", "bmi")]
data2 <- nhanes[, c("hyp", "chl")]
imp1 <- mice(data1, m = 2, maxit = 1, print = FALSE)
imp2 <- mice(data2, m = 2, maxit = 1, print = FALSE)

# Append two solutions
imp12 <- cbind(imp1, imp2)

# This is a different imputation model
imp12$predictorMatrix

# Append the other way around
imp21 <- cbind(imp2, imp1)
imp21$predictorMatrix

# Append 'forgotten' variable chl
data3 <- nhanes[, 1:3]
imp3 <- mice(data3, maxit = 1, m = 2, print = FALSE)
imp4 <- cbind(imp3, chl = nhanes$chl)

# Of course, chl was not imputed
head(complete(imp4))

# Combine mids object with data frame
imp5 <- cbind(imp3, nhanes2)
head(complete(imp5))

mice documentation built on Nov. 14, 2020, 5:07 p.m.

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