mice (version 2.14)

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,ANY':
plot(x, y, \dots)
plot.mids(x, y=NULL, theme=mice.theme(),
                        layout=c(2,3), type="l", col=1:10, lty=1,
                        ...)

Arguments

x, object

A object of class mids.

y

A character vector containing variable names, an integer vector of indices of imputed variables, a logical vector of length(dimnames(x$chainMean[,,1])[[1]]), or a formula. The result of the evaluation will be plotted in the trace plot.

theme

List of settings with selected graphical parameters to control the lattice function xyplot().

layout

Vector of two numbers controlling the number of panels in horizontal and vertical direction, respectively.

type

Plot type parameter.

col

Color parameter.

lty

Line type parameter.

...

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.

References

van Buuren S and Groothuis-Oudshoorn K (2011). mice: Multivariate Imputation by Chained Equations in R. Journal of Statistical Software, 45(3), 1-67. http://www.jstatsoft.org/v45/i03/

See Also

mice, mira, mipo