mi: 06pool – R documentation

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06pool

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.

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)

mi

Missing Data Imputation and Model Checking

v1.0

GPL (>= 2)

Authors

Andrew Gelman [ctb], Jennifer Hill [ctb], Yu-Sung Su [aut], Masanao Yajima [ctb], Maria Pittau [ctb], Ben Goodrich [cre, aut], Yajuan Si [ctb], Jon Kropko [aut]

Initial release

2015-04-16