R - 将因子的参考水平设置为 NA

Question

我有一个 data.table，其中一些值为 NA 的因子列。我特意将 NA 作为因子水平（即 x <- factor(x, exclude=NULL)，而不是 x <- factor(x, exclude=NA) 的默认行为），因为 NA 对我的模型有意义。对于这些因子列，我希望 relevel() 参考水平为 NA，但我在语法上苦苦挣扎。

# silly reproducible example
library(data.table)
a <- data.table(animal = c("turkey","platypus","dolphin"),
            mass_kg = c(8, 2, 200),
            egg_size= c("large","small",NA),
            intelligent=c(0,0,1)
            )
lr <- glm(intelligent ~ mass_kg + egg_size, data=a, family = binomial)
summary(lr) 

# By default, egg_size is converted to a factor with no level for NA
# However, in this case NA is meaningful (since most mammals don't lay eggs)

a[,egg_size:=factor(egg_size, exclude=NULL) ] # exclude=NULL allows an NA level

lr <- glm(intelligent ~ mass_kg + egg_size, data=a, family = binomial)
summary(lr) # Now NA is included in the model, but not as the reference level

a[,levels(egg_size)] # Returns: [1] "large" "small" NA    

a[,egg_size:=relevel(egg_size,ref=NA)]
# Returns:
# Error in relevel.factor(egg_size, ref = NA) : 
#   'ref' must be an existing level

relevel() 的正确语法是什么，还是我需要使用其他语法？非常感谢。

Answer 1

您必须指定正确的 NA 类型，即 NA_character_，但这样会抛出 NA，这可能是一个错误。解决方法是自己直接指定级别：

# throw out NA's to begin with
egg_size = factor(c("large","small",NA), exclude = NA)

# but then add them back at the beginning
factor(egg_size, c(NA, levels(egg_size)), exclude = NULL)
#[1] large small <NA> 
#Levels: <NA> large small

如果您想知道，c 将 NA 从 logical.

转换为正确的类型

R - 将因子的参考水平设置为 NA

R - set reference level of factor to NA

r

categorical-data

r-factor