R: Estimate a Model Pooling Over the Imputed Datasets
06pool
R Documentation
Estimate a Model Pooling Over the Imputed Datasets
Description
This function estimates a chosen model, taking into account the additional
uncertainty that arises due to a finite number of imputations of the missing
data.
Usage
pool(formula, data, m = NULL, FUN = NULL, ...)
Arguments
formula
a formula in the same syntax as used by glm
data
an object of mi-class
m
number of completed datasets to average over, which if NULL defaults to
the number of chains used in mi
FUN
Function to estimate models or NULL which uses the same function as
used in the fit_model-methods for the dependent variable
...
further arguments passed to FUN
Details
FUN is estimated on each of the m completed datasets according to the given
formula and the results are combined using the Rubin Rules.
Value
An object of class "pooled" whose definition is subject to change but it has a
summary and display method.
Author(s)
Ben Goodrich and Jonathan Kropko, for this version, based on earlier versions written by Yu-Sung Su, Masanao Yajima,
Maria Grazia Pittau, Jennifer Hill, and Andrew Gelman.
See Also
mi
Examples
if(!exists("imputations", env = .GlobalEnv)) {
imputations <- mi:::imputations # cached from example("mi-package")
}
analysis <- pool(ppvtr.36 ~ first + b.marr + income + momage + momed + momrace,
data = imputations)
display(analysis)