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Missing Confidence Intervals on a Geom_smooth function with double y graph

Time:11-24

I am struggling to make a graph with double y axis. It comes out without confidence intervals with loess and I am not able to understand the reason.

Below I am reporting the code:

library(ggplot2)
library(readxl)

Dati  <- data.frame("r" = c(0.99, 1.42, 2.10, 3.32, 6.09), "Vix" = c(16500, 19200, 22500, 24000, 26000), "OT" = c(23.5, 19, 11, 9, 7), "ref" = c("PU 178", "PU 178", "PU 178", "PU 178", "PU 178"))
attach(Dati)


scaleFactor <- max(Vix) / max(OT)


Graph <- ggplot(Dati, aes(x= r))  
  geom_point(aes(y= Vix, col=paste0("Vix ", ref)), shape = 1, size = 3.5)  
  geom_smooth(aes(y= Vix, col = paste0("Vix ", ref)),  method="loess", level=0.55, se = TRUE)    
  geom_point(aes(y= OT * scaleFactor, col=paste0("OT ", ref)), shape = 1, size = 3.5)   
  geom_smooth(aes(y=OT * scaleFactor, col = paste0("OT ", ref)), method="loess", level=0.55, se = TRUE)    
  scale_color_manual(values=c('#644196', '#f92410', '#bba6d9',  '#fca49c'),
                     name = "")  

theme(legend.justification = "top")  

  scale_y_continuous(name="Viscosity at 10rpm (mPa s)", sec.axis=sec_axis(~./scaleFactor, name="open time (sec)"))  
  theme(
    axis.title.y.left=element_text(color='#f92410'),
    axis.text.y.left=element_text(color='#f92410'),
    axis.title.y.right=element_text(color='#644196'),
    axis.text.y.right=element_text(color='#644196'),
    legend.position = "none"
  )   
  scale_x_continuous(name="ratio A2333/AD5027") 

Graph

And the result is completely without CI for both lines. I thought it was too big or small the specified level but also changing it I get no CIs. I thought 5 values are too less to achieve, but I made in the past graph with 5 values without problems.

Does somebody know if I made any mistake?

Below I post the graph which I obtain.

enter image description here

Do

CodePudding user response:

Your span is too small (see enter image description here

Loess is a bit of an overkill here, you can consider other enter image description here

Or polynomial of degree 2:

Dati %>% mutate(OT = OT*scaleFactor) %>%
pivot_longer(-c(r,ref)) %>%
mutate(name = paste0(name,ref)) %>%
ggplot(aes(x = r,y = value,col = name,fill = name))  
geom_point(shape = 1, size = 3.5)  
geom_smooth(method="lm",formula = y ~ poly(x, 2),alpha=0.1)  
theme_bw()

enter image description here

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