R:用lmer预测，y~.公式错误

Question

当使用句点表示预测因子时，从lmer模型预测新数据中的值会引发错误。有办法解决这个问题吗？

这个类似问题的答案提供了一种自动写出完整公式的方法，而不是使用句号，但我很好奇是否有办法只使用句号从新数据中获得预测。

这里有一个可重复的例子：

mydata <- data.frame(
groups = rep(1:3, each = 100),
x = rnorm(300),
dv = rnorm(300)
)
train_subset <- sample(1:300, 300 * .8)
train <- mydata[train_subset,]
test <- mydata[-train_subset,]
# Returns an error
mod <- lmer(dv ~ . - groups + (1 | groups), data = train)
predict(mod, newdata = test)
predict(mod) # getting predictions for the original data works
# Writing the full formula without the period does not return an error, even though it's the exact same model
mod <- lmer(dv ~ x + (1 | groups), data = train)
predict(mod, newdata = test)

Answer 1

现在应该在lme4的开发分支中解决这个问题。您可以从GitHub安装(见下面的第一行(，也可以等待几周(4月初(，等待新版本进入CRAN。

remotes::install_github("lme4/lme4") ## you will need compilers etc.
mydata <- data.frame(
groups = rep(1:3, each = 100),
x = rnorm(300),
dv = rnorm(300)
)
train_subset <- sample(1:300, 300 * .8)
train <- mydata[train_subset,]
test <- mydata[-train_subset,]
# Returns an error
mod <- lmer(dv ~ . - groups + (1 | groups), data = train)
p1 <- predict(mod, newdata = test)
mod2 <- lmer(dv ~ x + (1 | groups), data = train)
p2 <- predict(mod2, newdata = test)
identical(p1, p2) ## TRUE