对R的MICE中的每个估算数据集执行操作 [英] Perform operation on each imputed dataset in R's MICE

问题描述

如何从R的软件包mice中对类mids的对象中的每个估算数据集执行操作(如子集或添加计算列)?我希望结果仍然是mids对象.

How can I perform an operation (like subsetting or adding a calculated column) on each imputed dataset in an object of class mids from R's package mice? I would like the result to still be a mids object.

示例

library(mice)
data(nhanes)

# create imputed datasets
imput = mice(nhanes)

估算的数据集存储为列表列表

The imputed datasets are stored as a list of lists

imput$imp

其中仅存在针对给定变量进行插补的观测行.

where there are rows only for the observations with imputation for the given variable.

原始(不完整)数据集存储在此处:

The original (incomplete) dataset is stored here:

imput$data

例如，如何在每个估算数据集中创建一个以chl/2计算的新变量，从而产生一个新的mids对象?

For example, how would I create a new variable calculated as chl/2 in each of the imputed datasets, yielding a new mids object?

推荐答案

另一个选择是在插补之前计算变量并对其进行限制.

Another option is to calculate the variables before the imputation and place restrictions on them.

library(mice)

# Create the additional variable - this will have missing
nhanes$extra <- nhanes$chl / 2

# Change the method of imputation for extra, so that it always equals chl/2
# change the predictor matrix so only chl predicts extra
ini <- mice(nhanes, max = 0, print = FALSE)

meth <- ini$meth
meth["extra"] <- "~I(chl/2)"

pred <- ini$pred  # extra isnt used to predict
pred[ "extra", "chl"] <- 1

# Imputations
imput <- mice(nhanes, seed=1, pred = pred, meth = meth, print = FALSE)

在老鼠中有一些例子:R中的链式方程进行多元插补

There are examples in mice: Multivariate Imputation by Chained Equations in R

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