虽然主效应的方向可以从估计的符号来解释,但交互作用效应的解释通常需要绘图。这个任务由R包sjPlot
来完成。例如,使用plot_model
函数,我绘制了两个连续变量之间的相互作用。
library(lme4)
#> Loading required package: Matrix
library(sjPlot)
#> Learn more about sjPlot with 'browseVignettes("sjPlot")'.
library(ggplot2)
theme_set(theme_sjplot())
# Create data partially based on code by Ben Bolker
# from https://stackoverflow.com/a/38296264/7050882
set.seed(101)
spin = runif(800, 1, 24)
trait = rep(1:40, each = 20)
ID = rep(1:80, each = 10)
testdata <- data.frame(spin, trait, ID)
testdata$fatigue <-
testdata$spin * testdata$trait /
rnorm(800, mean = 6, sd = 2)
# Model
fit = lmer(fatigue ~ spin * trait + (1|ID),
data = testdata, REML = TRUE)
#> boundary (singular) fit: see help('isSingular')
plot_model(fit, type = 'pred', terms = c('spin', 'trait'))
#> Warning: Ignoring unknown parameters: linewidth
创建于2023-06-24带有reprex v2.0.2
1条答案
按热度按时间b09cbbtk1#
下面是一个使用自定义函数
deciles_interaction_plot
和sextiles_interaction_plot
的解决方案,来自https://pablobernabeu.github.io/2022/plotting-two-way-interactions-from-mixed-effects-models-using-ten-or-six-bins创建于2023-06-24带有reprex v2.0.2