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)
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. - imputationMethodA 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.
- 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. - chainCovA list with similar structure of itermean, 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, C.G.M. (2000)
Multivariate Imputation by Chained Equations: MICE V1.0 User's manual.
Leiden: TNO Quality of Life.
http://www.stefvanbuuren.nl/publications/MICE V1.0 Manual TNO00038 2000.pdf