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mice (version 2.14)

mipo: Multiply Imputed Pooled Analysis

Description

The mipo object is generated by the pool function from a link{mira} object. The mipo class of objects has methods for the following generic functions: print, summary.

Usage

is.mipo(x)
## S3 method for class 'mipo':
print(x,\dots)
## S3 method for class 'mipo':
summary(object,\dots)

Arguments

x, object
An object of class mira containing the m fit objects of a complete data analysis, plus some additional information.
...
not used.

Value

  • callThe call that created the mipo object.
  • call1The call that created the mira object that was used in call.
  • call2The call that created the mids object that was used in call1.
  • nmisAn array containing the number of missing observations per column.
  • mNumber of multiple imputations.
  • qhatAn m by npar matrix containing the complete data estimates for the npar parameters of the m complete data analyses.
  • uAn m by npar by npar array containing the variance-covariance matrices of the m complete data analyses.
  • qbarThe average of complete data estimates.
  • ubarThe average of the variance-covariance matrix of the complete data estimes.
  • bThe between imputation variance-covariance matrix.
  • tThe total variance-covariance matrix.
  • rRelative increases in variance due to missing data.
  • dfcomDegrees of freedom in the hypothetically complete data: the sample size minus the number of free parameters.
  • dfDegrees of freedom associated with the t-statistics.
  • fmiFraction of missing information.
  • lambdaProportion of the variation attributable to the missing data: (b+b/m)/t.

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

pool, mids, mira