mice (version 1.14)

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

## S3 method for class 'mids':
print(x, \dots)
## S3 method for class 'mids':
summary(object, \dots)
## S3 method for class 'mids':
plot(x, y, \dots)

Arguments

x

A mids object.

object

A mids object.

y

Not used.

...

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.
• imputationMethod
  A vector of strings of length(nvar) specifying the elementary imputation method per column.
• predictorMatrix
  A square matrix of size ncol(data) containing 0/1 data specifying the predictor set.
• visitSequence
  The sequence in which columns are visited.
• 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.
• chainCov
  A list with similar structure of itermean, 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. & Oudshoorn, C.G.M. (2000). Multivariate Imputation by Chained Equations: MICE V1.0 User's manual. Report PG/VGZ/00.038, TNO Prevention and Health, Leiden.