mice (version 2.46.0)

mipo-class: Multiply imputed pooled analysis (mipo)

Description

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

Arguments

Slots

.Data:

Object of class "list" containing the following slots:

call:

The call that created the mipo object.

call1:

The call that created the mira object that was used in call.

call2:

The call that created the mids object that was used in call1.

data:

A copy of the incomplete data set.

nmis:

An array containing the number of missing observations per column.

m:

Number of multiple imputations.

qhat:

An m by npar matrix containing the complete data estimates for the npar parameters of the m complete data analyses.

u:

An m by npar by npar array containing the variance-covariance matrices of the estimates of the m complete data analyses.

qbar:

The average of complete data estimates. The multiple imputation estimate.

ubar:

The average of the variance-covariance matrix of the complete data estimates.

b:

The between imputation variance-covariance matrix for the estimates.

t:

The total variance-covariance matrix for the estimates.

r:

Relative increases in variance due to missing data.

dfcom:

Degrees of freedom in the hypothetically complete data: the sample size minus the number of free parameters.

df:

Degrees of freedom associated with the t-statistics.

fmi:

Fraction of missing information.

lambda:

Proportion 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