Adding R squared value to orthogonal regression line in R

Question

I have produced a scatter plot in R of expected/observed values. I calculated orthogonal regression and added the line using the following:

library(ggplot2)
library(MethComp)

r<-read_csv("Uni/MSci/Project/DATA/new data sheets/comparisons/for comarison 
graphs/R Regression/GCdNi.csv")
x<-r[1]
y<-r[2]

P<-ggplot()+geom_point(aes(x=x,y=y))+ 
scale_size_area()+xlab("Expected")+ylab("Observed")+ggtitle("G - Cd x Ni")+ 
xlim(0, 40)+ylim(0, 40)

# Orthogonal, total least squares or Deming regression
deming <- Deming(y=r$Observed, x=r$Expected)[1:2]
deming  

R <- prcomp( ~ r$Expected + r$Observed )
slope <- R$rotation[2,1] / R$rotation[1,1]
slope   

intercept <- R$center[2] - slope*R$center[1]
intercept

#Plot orthogonal regression
P+geom_abline(intercept = deming[1], slope = deming[2])

This gives me the following plot:

Is there a way I can calculate and add an R squared value to the graph?

Heres some of the data frame to allow for reproduction:

Expected    Observed
2.709093153 1.37799781
2.611562579 1.410720257
2.22411805  1.287685907
3.431914392 1.906787706
3.242018129 1.823698676
3.46139841  1.767857729
2.255673738 1.111307235
2.400606765 1.294583377
1.818447253 0.995226256
2.528992184 1.173159775
2.46829393  1.101852756
1.826044939 0.883336715
1.78702201  1.050122993
2.37226253  1.025298403
2.140921846 1.094761918

score 3 · Answer 1 · answered Mar 21 '18 at 14:14

I could not reproduce your data, but here's how you could do something like that with linear regression.

library(ggplot2)
set.seed(1)
x <- rnorm(20,1,100)
y<- x + rnorm(20,50,10)

regression <- lm(y ~ x)
r2 <- summary(regression)$r.squared

ggplot() + geom_point(aes(x, y)) +
    geom_line(aes(x, regression$fitted.values)) +
    annotate("text", x = -100, y = 200, label = paste0("r squared = ", r2))

In the future, you should provide a reproducible example.

Adding R squared value to orthogonal regression line in R

1 Answers1