使用 sjPlot 绘制 glmer 模型

Question

df <- data.frame(C=c(1,1,1,1,2,2,2,2,3,3,3,3,4,4,4,4,5,5,5,5,6,6,6,6,7,7,7,7,8,8,8,8), 
                 Y=c("F","F","F","F","F","F","F","F","F","F","F","F","F","F","F","F",
                     "M","M","M","M","M","M","M","M","M","M","M","M","M","M","M","M"), 
                 B=c(1,1,3,2,5,3,6,7,2,1,2,4,3,2,3,6,8,6,5,8,5,7,4,8,7,8,2,9,7,7,6,7))

m <- glmer(Y ~ B + (1|C), data=df, family=binomial())

plot_model(m)

我希望获得与 here 所示类似的概率曲线图。

我怎样才能做到这一点？

Answer 1

只有一个固定效应协变量 ($B)，因此在阅读 plot_model 的帮助页面并与您提供的过时 material 进行比较后。这似乎提供了所要求的情节：

> plot_model(m, type = "pred")
$B

在尝试从 Github 获取最新版本的 sjPlot 及其依赖项的所有当前版本，然后阅读当前帮助页面并测试上面的代码后，我现在明白了@Marius 已经发布了这个。那好吧。如果他要回复我就删

使用 sjPlot 绘制 glmer 模型

plotting glmer model with sjPlot

plot

r

lme4

mixed-models