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mice (version 1.16)

mipo: Multiply Imputed Pooled Analysis

Description

The "mipo" object is generated by the lm.mids and glm.mids functions. The "mipo" class of objects has methods for the following generic functions: print, summary.

Usage

print.mipo(x,...)
summary.mipo(object,...)

Arguments

x, object
An object 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 x npar matrix containing the complete data estimates for the npar paremeters of the m complete data analyses.
  • uAn m x npar x 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
  • dfDegrees of freedom associated with the t-statistics.
  • fFractions of missing information.

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.