CODEWITHSUNDEEP
rggplot2confidence-interval
GiacomoDB
GiacomoDB

Reputation: 469

Missing Confidence Intervals on a Geom_smooth function with double y graph

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

Upvotes: 1

Views: 946

Answers (1)

StupidWolf
StupidWolf

Reputation: 46978

Your span is too small (see this), so there's too little points to estimate your confidence interval. So for example if you do:

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" ,span=1) +  
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",span=1) +  
scale_color_manual(values=c('#644196', '#f92410', '#bba6d9',  '#fca49c'),
                     name = "") +

theme(legend.justification = "top")

enter image description here

Loess is a bit of an overkill here, you can consider other smooth and also pivoting your data long to make it easier to code:

library(tidyr)
library(dplyr)

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="gam",formula = y ~ s(x,k=3),alpha=0.1) +
theme_bw()

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

Upvotes: 1

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