QBoard » Statistical modeling » Stats - Tech » Adding Regression Line Equation and R2 on graph
User Dashboard

Adding Regression Line Equation and R2 on graph

Back To Topics
Tags : #R #ggplot2  #ggpmisc
  • 102 9
     
    I wonder how to add regression line equation and R^2 on the ggplot. My code is

    library(ggplot2)

df <- data.frame(x = c(1:100))
df$y <- 2 + 3 * df$x + rnorm(100, sd = 40)
p <- ggplot(data = df, aes(x = x, y = y)) +
            geom_smooth(method = "lm", se=FALSE, color="black", formula = y ~ x) +
            geom_point()
p​

    Any help will be highly appreciated.
    This post was edited by Shivakumar Kota at September 22, 2020 3:53 PM IST
      May 23, 2019 1:00 PM IST
    0
  • 63 1

    Using ggpubr:

    library(ggpubr)

# reproducible data
set.seed(1)
df <- data.frame(x = c(1:100))
df$y <- 2 + 3 * df$x + rnorm(100, sd = 40)

# By default showing Pearson R
ggscatter(df, x = "x", y = "y", add = "reg.line") +
  stat_cor(label.y = 300) +
  stat_regline_equation(label.y = 280)




    # Use R2 instead of R
ggscatter(df, x = "x", y = "y", add = "reg.line") +
  stat_cor(label.y = 300, 
           aes(label = paste(..rr.label.., ..p.label.., sep = "~`,`~"))) +
  stat_regline_equation(label.y = 280)

## compare R2 with accepted answer
# m <- lm(y ~ x, df)
# round(summary(m)$r.squared, 2)
# [1] 0.85


      September 22, 2020 3:58 PM IST
    1
  • 131 2

    Here's the most simplest code for everyone

    Note: Showing Pearson's Rho and not R^2.

    library(ggplot2)
library(ggpubr)

df <- data.frame(x = c(1:100)
df$y <- 2 + 3 * df$x + rnorm(100, sd = 40)
p <- ggplot(data = df, aes(x = x, y = y)) +
        geom_smooth(method = "lm", se=FALSE, color="black", formula = y ~ x) +
        geom_point()+
        stat_cor(label.y = 35)+ #this means at 35th unit in the y axis, the r squared and p value will be shown
        stat_regline_equation(label.y = 30) #this means at 30th unit regresion line equation will be shown


      September 22, 2020 4:02 PM IST
    1
  • 129 8
     Here is one solution
    # GET EQUATION AND R-SQUARED AS STRING
# SOURCE: https://groups.google.com/forum/#!topic/ggplot2/1TgH-kG5XMA

lm_eqn <- function(df){
    m <- lm(y ~ x, df);
    eq <- substitute(italic(y) == a + b %.% italic(x)*","~~italic(r)^2~"="~r2, 
         list(a = format(unname(coef(m)[1]), digits = 2),
              b = format(unname(coef(m)[2]), digits = 2),
             r2 = format(summary(m)$r.squared, digits = 3)))
    as.character(as.expression(eq));
}

p1 <- p + geom_text(x = 25, y = 300, label = lm_eqn(df), parse = TRUE)​

    EDIT. I figured out the source from where I picked this code. Here is the link to the original post in the ggplot2 google groups

    Output

    This post was edited by Rakesh Racharla at September 22, 2020 3:55 PM IST
      May 23, 2019 1:04 PM IST
    0
  • 53
    I changed a few lines of the source of stat_smooth and related functions to make a new function that adds the fit equation and R squared value. This will work on facet plots too!

    library(devtools)
source_gist("524eade46135f6348140")
df = data.frame(x = c(1:100))
df$y = 2 + 5 * df$x + rnorm(100, sd = 40)
df$class = rep(1:2,50)
ggplot(data = df, aes(x = x, y = y, label=y)) +
  stat_smooth_func(geom="text",method="lm",hjust=0,parse=TRUE) +
  geom_smooth(method="lm",se=FALSE) +
  geom_point() + facet_wrap(~class)

    enter image description here

      October 14, 2020 5:58 PM IST
    0