mipo: Multiple imputation pooled objectThe 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/