r - 使用来自库 mouse() 的估算数据集来拟合 R 中的多级模型

Question

我是新来的包裹 mice在 R 中。但我试图从 popmis 估算 5 个数据集然后安装一个 lmer()型号 with()最后pool()穿过他们。
我认为pool()函数在 mice()不适用于 lmer()来自 lme4 的来电包，对吗？
如果是这种情况，有没有办法编写一个自定义函数，其作用类似于 pool()对于我下面的情况？

library(mice)
library(lme4)

imp <- mice(popmis, m = 5) # `popmis` is a dataset from `mice`

fit <- with(imp, lme4::lmer(popular ~ sex + (1|school))) # works fine.

pool(fit) # BUT this one fails, should I loop here?

Answer 1

我有你的解决方案。就像install.packages("broom.mixed")一样简单然后 library(broom.mixed) . broom.mixed包提供了正确的 glance方法

# install.packages("broom.mixed")
library(mice)
library(lme4)
library(broom.mixed)
imp <- mice(popmis, m = 5) # `popmis` is a dataset from `mice`

fit <- with(data = imp, exp = lme4::lmer(popular ~ sex + (1|school)))

pool(fit) 

结果:

> pool(fit)
Class: mipo    m = 5 
         term m  estimate        ubar            b           t dfcom       df        riv     lambda        fmi
1 (Intercept) 5 4.9122016 0.007589694 0.0003823641 0.008048531  1996 743.8691 0.06045526 0.05700878 0.05953397
2         sex 5 0.8378947 0.001187606 0.0002937859 0.001540149  1996  72.7305 0.29685175 0.22890184 0.24926611

Ben Bolker is the author of broom.mixed