首先,我使用您提供的数据复制您的情节:
library(dplyr)
library(readr)
library(nnet)
library(sjPlot)
"ASA,DSA,Info_Sought
-0.108555801,0.659899854,First Pic
0.671946671,1.481880373,First Pic
2.184170211,-0.801398848,First Pic
-0.547588442,1.116555698,First Pic
-1.27930951,-0.299077419,First Pic
0.037788412,1.527545958,First Pic
-0.74271406,-0.755733264,Multiple Pics
1.20854212,-1.166723523,Multiple Pics
0.769509479,-0.390408588,Multiple Pics
-0.450025633,-1.02972677,Multiple Pics
0.769509479,0.614234269,Multiple Pics
0.281695434,0.705565438,Multiple Pics
-0.352462824,-0.299077419,Expand
0.671946671,1.481880373,Expand
2.184170211,-0.801398848,Expand
-0.547588442,1.116555698,Expand
-0.157337206,1.070890114,Expand
-1.27930951,-0.299077419,Expand" %>%
read_csv() -> d
multinomialmodel <- multinom(Info_Sought ~ ASA + DSA, data = d)
p1 <- plot_model(multinomialmodel ,
type = "pred",
terms = c("DSA", "ASA[meansd]"))
p1
您的重构尝试没有奏效,因为sjPlot::plot_model()
没有注意。解决对构面重新排序的一种方法是生成如上所述的初始图,并将数据中的构面变量替换为包含所需顺序的因子版本,如下所示:
p2 <- p1
p2$data$response.level <- factor(p2$data$response.level,
levels = c("Multiple Pics", "First Pic", "Expand"))
p2
最后,为了解决图例标签问题,我们可以将色标替换为包含所需标签的色标:
p2 +
scale_color_discrete(labels = c("-1 SD", "mean", "+1 SD"))