bootMice: Bootstrap then impute using mice

In jwb133/bootmi: Bootstrap Inference for Multiple Imputation

Bootstrap then impute using mice

Description

Bootstraps an incomplete dataset and then imputes each bootstrap a number of times using the mice package. The resulting list of bootstrapped then imputed datasets can be analysed with bootImputeAnalyse. To run this function requires the mice package to be installed.

Usage

bootMice(obsdata, nBoot = 200, nImp = 2, nCores = 1, seed = NULL, ...)

Arguments

obsdata	The data frame to be imputed.
nBoot	The number of bootstrap samples to take. It is recommended that you use a minimum of 200. If you specify nCores>1, nBoot must be a multiple of the specified nCores value.
nImp	The number of times to impute each bootstrap sample. Two is recommended.
nCores	The number of CPU cores to use. If specified greater than one, bootImpute will impute using the number of cores specified.
seed	Random number seed.
...	Other arguments that are to be passed to mice.

Value

A list of imputed datasets.

Examples

library(mice)

head(linquad)

#bootstrap 10 times and impute each twice
imps <- bootMice(linquad, nBoot=10, nImp=2, seed=564764)

jwb133/bootmi documentation built on June 9, 2025, 4:58 p.m.