Learn R Programming

mice (version 2.7)

mids: 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

is.mids(x)
## S3 method for class 'mids':
print(x,\dots)
## S3 method for class 'mids':
summary(object,\dots)
## S3 method for class 'mids':
plot(x, y = 0, layoutplot = c(3, 2), askplot = TRUE, ...)

Arguments

x, object
A object of class mids.
y
Not used.
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

  • callThe call that created the object.
  • dataA copy of the incomplete data set.
  • mThe number of imputations.
  • nmisAn array containing the number of missing observations per column.
  • impA 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.
  • methodA vector of strings of length(nvar) specifying the elementary imputation method per column.
  • predictorMatrixA square matrix of size ncol(data) containing code 0/1 data specifying the predictor set.
  • visitSequenceThe sequence in which columns are visited.
  • postA vector of strings of length ncol(data) with commands for post-processing
  • seedThe seed value of the solution.
  • iterationLast Gibbs sampling iteration number.
  • lastSeedValueThe most recent seed value.
  • chainMeanA 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.
  • chainVarA list with similar structure of chainMean, containing the covariances of the imputed values.
  • padA 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.

References

Van Buuren, S., Groothuis-Oudshoorn, K. (2010) 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