如何在R语言effects包的effect函数中自定义变量f3的取值？

嘿，这个问题其实很好解决——effects包的effect()函数自带了自定义变量取值的参数，不用大改代码就能实现你要的效果。我给你具体说明：

核心方法：使用xlevels参数 #

effect()函数里的xlevels参数可以让你手动指定某个变量的取值，只需要传入一个列表，把要自定义的变量名作为键，你想要的取值向量作为值就行。

修改后的完整代码 #

# 先构建原始数据和模型（和你的代码一致）
sub <- c(1,1,2,2,3,3,4,4,5,5,6,6,7,7,8,8,9,9,10,10,11,11,12,12,13,13,14,14,15,15,16,16,17,17,18,18,19,19,20,20)
f1 <- c("f","f","f","f","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","m","m","m","m")
f2 <- c("c1","c1","c1","c1","c1","c1","c1","c1","c1","c1","c2","c2","c2","c2","c2","c2","c2","c2","c2","c2","c1","c1","c1","c1","c1","c1","c1","c1","c1","c1","c2","c2","c2","c2","c2","c2","c2","c2","c2","c2")
f3 <- c(0.03,0.03,0.49,0.49,0.33,0.33,0.20,0.20,0.13,0.13,0.05,0.05,0.47,0.47,0.30,0.30,0.22,0.22,0.15,0.15, 0.03,0.03,0.49,0.49,0.33,0.33,0.20,0.20,0.13,0.13,0.05,0.05,0.47,0.47,0.30,0.30,0.22,0.22,0.15,0.15)
y <- c(0.9,1,98,96,52,49,44,41,12,19,5,5,89,92,65,56,39,38,35,33, 87,83,5,7,55,58,67,61,70,80,88,90,0.8,0.9,55,52,55,58,70,69)
dat <- data.frame(sub=sub, f1=f1, f2=f2, f3=f3, y=y)
m <- lmer(y ~ f1*f2*f3 + (1|sub), data=dat)

library(effects)

# 自定义f3的取值
custom_f3_values <- c(0.04, 0.20, 0.50)
# 在effect()中指定xlevels参数
fit <- effect('f1:f3', m, xlevels = list(f3 = custom_f3_values))
fit_df <- as.data.frame(fit)

# 查看结果的f3列，确认是自定义的取值
head(fit_df)

关键细节说明 #

• xlevels是一个列表，你可以同时自定义多个变量的取值，比如如果要调整f1的水平（虽然这里它是分类变量，默认会取所有水平），可以写成xlevels = list(f3 = custom_f3_values, f1 = c("f"))
• 对于连续变量f3，默认情况下effects包会自动选取5个代表性取值（比如分位数或等间隔值），用xlevels就可以完全覆盖这个默认行为
• 运行后你会发现fit_df中的f3列完全是你指定的0.04、0.20、0.50，和f1的各个水平组合生成结果

内容的提问来源于stack exchange，提问作者locus