Force geom_smooth() to plot regression line from origin to one set of points (R, ggplot, geom

I have a very specific situation where I am trying to get a regression line to start at the origin and fit to one set of points on the x axis. Ideally I wouldn't have to do this but the line from the origin to these points is actually meaningful in my case.

I have come up with a simple example

library(dplyr)
library(ggplot2)
y<-c(1,2,3,4,5,6,7,8)
x<-c(3,3,3,3,3,3,3,3)
z<-as.data.frame(cbind(x,y))
z %>% ggplot(aes(x,y))   geom_point()   
  geom_smooth(formula = y ~ x   0, method = "lm")  
  theme_bw()   expand_limits(x = 0, y = 0)    
  theme(aspect.ratio = 1)

enter image description here

Here, geom smooth will not fit a line from the origin to the points at x = 3. I'm assuming that there is some background script telling geom smooth to not plot a line where no variation in x axis exists. I've tested this somewhat and by changing one of the x values to 0 I can indeed get a line from the origin (though the y value I choose influences the confidence interval which is not ideal).

y<-c(1,2,3,4,5,6,7,8)
x<-c(3,3,3,3,3,3,3,0)
z<-as.data.frame(cbind(x,y))
z %>% ggplot(aes(x,y))   geom_point()   
  geom_smooth(formula = y ~ x   0, method = "lm")  
  theme_bw()   expand_limits(x = 0, y = 0)   
  theme(aspect.ratio = 1)

enter image description here

I don't want to fiddle with the dataset and add a point at y = 0, x = 0 as I'm worried about that influencing some error estimate (however small). I'm assuming that there is some condition that I can set within geom smooth or some other command to force the line to fit. Any help is appreciated, thanks

CodePudding user response：

Remember that linear regression just tells you the conditional mean of y for a given x. The "regression" at x = 3 is simply the best estimate of the mean of y at x = 3. Since all of your points are at x = 3, the conditional mean of y when x = 3 is just mean(y)

So all you need should be a line going from (0, 0) to (0, mean(y)). It really doesn't make any sense to have a standard error around this line, though perhaps it might be justified depending on the context.

library(dplyr)
library(ggplot2)
y<-c(1,2,3,4,5,6,7,8)
x<-c(3,3,3,3,3,3,3,3)
z<-as.data.frame(cbind(x,y))
z %>% ggplot(aes(x,y))   geom_point()   
  geom_smooth(formula = y ~ x   0, method = "lm")  
  theme_bw()   expand_limits(x = 0, y = 0)    
  theme(aspect.ratio = 1)  
  geom_line(data = data.frame(x = c(0, 3), y = c(0, mean(y))))

CodePudding user response：

Kind of silly but workable solution that I have figured out.

If I add an incredibly small amount of random variation to values in the x axis and specify fullrange = TRUE within geom_smooth then I can get the line to fit with an error estimate.

y<-c(1,2,3,4,5,6,7,8)
x<-c(3,3,3,3,3,3,3,3)
z<-as.data.frame(cbind(x,y))
z %>% mutate(rand = rnorm(8, mean=0.0000000001, sd=0.000000000001), x = x   rand) %>% 
  ggplot(aes(x,y))   geom_point()   
  geom_smooth(formula = y ~ x   0, fullrange = TRUE ,method = "lm")  
  theme_bw()   expand_limits(x = 0, y = 0)  
  theme(aspect.ratio = 1)