glmer AICcmodavg 的预测值

Question

我知道可以使用 AICcmodavg 获得预测值（以原始比例 ~ 概率）和固定效应的 SE，但我正在尝试但没有成功...有人可以帮助我吗？提前致谢

library(lme4)
(gm1 <- glmer(cbind(incidence, size - incidence) ~ period + (1 | herd),
              data = cbpp, family = binomial))
fixef(gm1)

library("AICcmodavg")

predictSE(gm1, 
          newdata=as.data.frame(period=c("period1","period2","period3","period4")), 
          type="response", 
          se.fit=TRUE, 
          level=0, 
          print.matrix=F)

Answer 1

最好读 levels(cbpp$period)，而不是 as.data.frame()，而是 data.frame()

levels(cbpp$period)
# [1] "1" "2" "3" "4"

predictSE(gm1, 
          newdata = data.frame(period=c("1", "2", "3", "4")),
          type = "response", 
          se.fit = TRUE, 
          level = 0, 
          print.matrix = F)

[已编辑]

查找错误原因的简单方法

fit <- ...(..., data = df)

predictSE(fit, newdata = df)
predictSE(fit, newdata = ...)

# If 1st predictSE() doesn't run, it means the model causes error.
# If 1st runs but 2nd doesn't, it means it is due to newdata.

如果您的模型有两个因素；

newd <- expand.grid(name1 = levels(df$name1), name2 = levels(df$name2))
predictSE(fit, newdata = newd)
 # pred <- predictSE(fit, newdata = newd)
 # cbind(newd, pred)            # help to interpret

glmer AICcmodavg 的预测值

predicted values for glmer AICcmodavg

r

predict

glm