将置信区间添加到交互的反向转换回归图中

如何解决将置信区间添加到交互的反向转换回归图中

我有一个混合效应模型，它 (a) 有一个对数链接，(b) 包括一个连续的交互。我想绘制交互效果，反向转换。我设法通过绘制 Y~X1 关系的三条线来做到这一点，每条线一条：平均 X2 -1SD、平均 X2 和平均 X2 + 1SD。但是，我真的需要在图中添加置信区间。 geom_ribbon 不能正常工作。任何人都可以帮忙吗？任何不使用 ggplot2 的建议也欢迎。这是没有置信区间的图的代码：

#the data

mydata<-structure(list(Week = c(3L,3L,6L,5L,1L,4L,2L,6L),X2 = c(20.8,21.4,22.2,21.9,21,21.8,16.6,15.6,19.8,17.5,12.5,20.1,20.5,21.7,22.3),X1 = c(78L,90L,81L,44L,9L,35L,99L,17L,7L,23L,14L,77L,84L,1L),Y = c(14.97469781,19.88267242,15.59780954,9.633809968,15.12038794,10.43636012,10.7436911,16.71840387,12.43274774,10.90741585,8.79514591,14.1932374,8.776376951,9.995133069,12.38314719,9.611533444)),class = "data.frame",row.names = c(NA,-16L))

attach(mydata)

#the model

Fmim<-glmer(Y~X1*X2+(1|Week),data=mydata,family=Gamma(link='log'))

E<-fixef(Fmim)

#set xf = to the mean X2 -1SD
xf=17.016

##then create a dummy variable
dummyx0<-seq(length=100,from=min(X1),to=max(X1))

##then create the y values from these dummy x values produced above
##because I logged the data,I have to do exponentiate the model to back-transform

y1x0<-(exp(E[1]+((E[3])*xf)+((E[2])*dummyx0)+((E[4])*xf*dummyx0)))



#set xf = to the mean X2
xf=19.85

#create the new y variable 

y2x0<-(exp(E[1]+((E[3])*xf)+((E[2])*dummyx0)+((E[4])*xf*dummyx0)))



#set xf = to the mean X2 + 1sD
xf=25.134


#create the new y variable

y3x0<-(exp(E[1]+((E[3])*xf)+((E[2])*dummyx0)+((E[4])*xf*dummyx0)))



plotdata1<-data.frame(x=dummyx0,y=y1x0)
plotdata2<-data.frame(x=dummyx0,y=y2x0)
plotdata3<-data.frame(x=dummyx0,y=y3x0)


ggplot(plotdata1)+
  geom_point(data = mydata,aes(x=X1,y=Y),size = 3.5,shape=1)+
  geom_line(data = plotdata1,aes(y=y1x0,x=dummyx0),size=1)+
  geom_line(data = plotdata2,aes(y=y2x0,size=1)+
  geom_line(data = plotdata3,aes(y=y3x0,size=1)+
  scale_colour_manual("",values="blue")+
  scale_fill_manual("",values="grey12")+
  labs(x=bquote("X1"),y = "Y") + 
  theme(panel.grid.major = element_blank(),panel.grid.minor = element_blank(),panel.background = element_blank(),axis.line = element_line(colour = "black"))+
  theme(legend.position ="none") +
  theme(axis.title = element_text(size=15),# for axix
        title = element_text(size=10),axis.text = element_text(size=15),axis.title.x = element_text(vjust = 0),axis.title.y = element_text(vjust = 2,hjust=0.5),legend.title = element_text(vjust = 0.5))