Adding the R-squared for a linear regression plot (ggplot2)?

Question

I've been trying different suggestions such as the ggmisc package, but nothing seems to work in my favor.

I'm using the iris dataframe and just trying to plot random variables:

modellm <- lm(`Sepal.Length` ~ `Sepal.Width` + `Petal.Length` + `Petal.Width`, data = iris) model <- coef(Modellm)["(Intercept)"] + coef(Modellm)["Sepal.Width"] * iris$`Sepal.Width` + coef(Modellm)["Petal.Length"] * iris$`Petal.Length` + coef(Modellm)["Petal.Width"] * iris$`Petal.Width` + residuals(Modellm) library(ggplot2) ggplot(iris, aes(`Sepal.Length`, model))+ geom_point(size=2, alpha=0.2)+ geom_smooth(method='lm')

How is it possible for me to get the R-squared value plotted in the ggplot?

What do you mean by "R-squared value plotted"?

jay.sf
– jay.sf

2018-07-09 08:54:49 +00:00
Commented Jul 9, 2018 at 8:54 — jay.sf
– jay.sf, Commented Jul 9, 2018 at 8:54

Shinobi_Atobe · Accepted Answer · 2018-07-09 08:56:41Z

If you want to display the r squared value just add this to the end of your plot:

 + annotate("text", x = 1, y = 1, label = paste0("R Squared = ", summary(modellm)$r.squared))

adjust the placement with the x and y coordinates

jay.sf · Accepted Answer · 2018-07-09 09:24:08Z

If you really want to plot the R^2, you could do something like this.

library(ggplot2) p <- ggplot(iris, aes(`Sepal.Length`, model))+ geom_point(size=2, alpha=0.2)+ geom_smooth(method='lm') r2 <- summary(Modellm)$r.squared p + scale_y_continuous( sec.axis=sec_axis(~ . * 4 / 30 , name = expression(paste(R^{2})))) + geom_rect(xmin=7.9, xmax=8, ymin=0, ymax=1*30/4, fill="white", color="#78B17E") + geom_rect(xmin=7.9, xmax=8, ymin=0, ymax=r2*30/4, fill="#78B17E") + annotate("text", x = 7.95, y = 7.62, size=3, color="#78B17E", label = paste0(round(r2, 2)))

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Adding the R-squared for a linear regression plot (ggplot2)?

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