mice (version 2.25)

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