mids {mice}R Documentation

Multiply Imputed Data Set

Description

An object containing a multiply imputed data set. The mids object is generated by the mice and mice.mids functions. The mids class of objects has methods for the following generic functions: print, summary, plot.

Usage

## S3 method for class 'mids':
print(x,...)
## S3 method for class 'mids':
summary(object,...)
## S3 method for class 'mids':
plot(x, layoutplot = c(3, 2), askplot = TRUE, ...)

Arguments

x, object A mids object.
layoutplot Vector of two integers specifying the number of panel per row and column respectively.
askplot TRUE if the user needs to be asked before drawing a new page
... Currently not used.

Value

call The call that created the object.
data A copy of the incomplete data set.
m The number of imputations.
nmis An array containing the number of missing observations per column.
imp A list of nvar components with the generated multiple imputations. Each part of the list is a nmis[j] by m matrix of imputed values for variable j.
method A vector of strings of length(nvar) specifying the elementary imputation method per column.
predictorMatrix A square matrix of size ncol(data) containing code 0/1 data specifying the predictor set.
visitSequence The sequence in which columns are visited.
post A vector of strings of length ncol(data) with commands for post-processing
seed The seed value of the solution.
iteration Last Gibbs sampling iteration number.
lastSeedValue The most recent seed value.
chainMean A list of m components. Each component is a length(visitSequence) by maxit matrix containing the mean of the generated multiple imputations. The array can be used for monitoring convergence. Note that observed data are not present in this mean.
chainVar A list with similar structure of chainMean, containing the covariances of the imputed values.
pad A list containing various settings of the padded imputation model, i.e. the imputation model after creating dummy variables. Normally, this array is only useful for error checking.

Author(s)

Stef van Buuren, Karin Groothuis-Oudshoorn, 2000

References

Van Buuren, S., Groothuis-Oudshoorn, K. (2009) MICE: Multivariate Imputation by Chained Equations in R. Journal of Statistical Software, forthcoming. http://www.stefvanbuuren.nl/publications/MICE in R - Draft.pdf

See Also

mice, mira, mipo


[Package mice version 2.2 Index]