mice (version 3.6.0)

mipo: mipo: Multiple imputation pooled object


The mipo object contains the results of the pooling step. The function pool generates an object of class mipo.


mipo(mira.obj, ...)

# S3 method for mipo summary(object, type = c("tests", "all"), conf.int = FALSE, conf.level = 0.95, exponentiate = FALSE, ...)

# S3 method for mipo print(x, ...)

# S3 method for mipo.summary print(x, ...)

process_mipo(z, x, conf.int = FALSE, conf.level = 0.95, exponentiate = FALSE)



An object of class mira

Arguments passed down


An object of class mipo


Logical indicating whether to include a confidence interval. The default is FALSE.


Confidence level of the interval, used only if conf.int = TRUE. Number between 0 and 1.


Flag indicating whether to exponentiate the coefficient estimates and confidence intervals (typical for logistic regression).


An object of class mipo


Data frame with a tidied version of a coefficient matrix


The summary method returns a data frame with summary statistics of the pooled analysis.


An object class mipo is a list with three elements: call, m and pooled.

The pooled elements is a data frame with columns:

estimate Pooled complete data estimate
ubar Within-imputation variance of estimate
b Between-imputation variance of estimate
t Total variance, of estimate
dfcom Degrees of freedom in complete data
df Degrees of freedom of $t$-statistic
riv Relative increase in variance
lambda Proportion attributable to the missingness
fmi Fraction of missing information

The names of the terms are stored as row.names(pooled).

The process_mipo is a helper function to process a tidied mipo object, and is normally not called directly. It adds a confidence interval, and optionally exponentiates, the result.


van Buuren S and Groothuis-Oudshoorn K (2011). mice: Multivariate Imputation by Chained Equations in R. Journal of Statistical Software, 45(3), 1-67. https://www.jstatsoft.org/v45/i03/

See Also

pool, mids, mira