调整回归线考虑 ggplot2 中的不同因素

如何解决调整回归线考虑 ggplot2 中的不同因素

我正在尝试重现下图，其中内部线是调整后的回归线：

然而，由于某些因素，它没有被绘制成它应该是的样子，也就是说，出现了一条线，而且，变量“teor”的不同浓度没有像图像中那样被绘制上面，看下面的结果：

数据：https://drive.google.com/file/d/1Y-GsNNcYINqtO-hcJfNRgaj545JZXZIS/view?usp=sharing

dados = read.table("datanew.csv",header = T,sep=";",dec=","); head(dados)
dados$Trat <- factor(dados$Trat)
dados$Teor <- factor(dados$Teor)
dadosnew$Tempo = as.factor(dadosnew$Tempo)

my.formula <- y ~ x
p = ggplot(dadosnew,aes(x = Tempo,y = massaseca,group = Fator)) +
  stat_summary(geom = "point",fun = mean) + 
  stat_smooth(method = "lm",se=FALSE,formula=y ~ poly(x,2,raw=TRUE)) + stat_poly_eq(formula = my.formula,eq.with.lhs = "As-italic(hat(y))~`=`~",aes(label = paste(..eq.label..,..rr.label..,sep = "*plain(\",\")~")),parse = TRUE,size = 5,label.y = 35)+
  labs(title = "",x = "Time (Minutes)",y = "Weight (mg)") + theme_bw() +
  theme(axis.title = element_text(size = 23,color="black"),axis.text = element_text(size = 18,text = element_text(size = 50,legend.position = "none") + facet_wrap(~Fator)
p 

解决方法

您需要另一个这样的分组变量：

#Code
my.formula <- y ~ x
ggplot(dadosnew,aes(x = Tempo,y = massaseca,group = interaction(Fator,Trat))) +
  stat_summary(geom = "point",fun = mean) + 
  stat_smooth(method = "lm",se=FALSE,formula=y ~ poly(x,2,raw=TRUE)) +
  stat_poly_eq(formula = my.formula,eq.with.lhs = "As-italic(hat(y))~`=`~",aes(label = paste(..eq.label..,..rr.label..,sep = "*plain(\",\")~")),parse = TRUE,size = 5,label.y = 35)+
  labs(title = "",x = "Time (Minutes)",y = "Weight (mg)") + theme_bw() +
  theme(axis.title = element_text(size = 23,color="black"),axis.text = element_text(size = 18,text = element_text(size = 50,legend.position = "none") + facet_wrap(~Fator)

输出：

作为研究人员，您应该定义哪些内容。