Adding Regression Line Equation and R2 on SEPARATE LINES graph

Question

A few years ago, a poster asked how to add regression line equation and R2 on ggplot graphs at the link below.

Adding Regression Line Equation and R2 on graph

The top solution was this:

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

I am using this code and it works great. However, I was wondering if it is at all possible to make this code have the R2 value and regression line equation on separate lines, instead of being separated by a comma.

Instead of like this

Something like this

Thanks in advance for your help!

Answer 1

ggpmisc package has stat_poly_eq function which is built specifically for this task (but not limited to linear regression). Using the same data as @Sathish posted, we can add the equation and R2 separately but give label.y.npc different values. label.x.npc is adjustable if desired.

library(ggplot2)
library(ggpmisc)
#> For news about 'ggpmisc', please, see https://www.r4photobiology.info/

set.seed(21318)
df <- data.frame(x = c(1:100))
df$y <- 2 + 3*df$x + rnorm(100, sd = 40)

formula1 <- y ~ x

ggplot(data = df, aes(x = x, y = y)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, formula = formula1) +
  stat_poly_eq(aes(label = paste(..eq.label.., sep = "~~~")), 
               label.x.npc = "right", label.y.npc = 0.15,
               eq.with.lhs = "italic(hat(y))~`=`~",
               eq.x.rhs = "~italic(x)",
               formula = formula1, parse = TRUE, size = 5) +
  stat_poly_eq(aes(label = paste(..rr.label.., sep = "~~~")), 
               label.x.npc = "right", label.y.npc = "bottom",
               formula = formula1, parse = TRUE, size = 5) +
  theme_bw(base_size = 16)

# using `atop`
ggplot(data = df, aes(x = x, y = y)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, formula = formula1) +
  stat_poly_eq(aes(label = paste0("atop(", ..eq.label.., ",", ..rr.label.., ")")), 
               formula = formula1, 
               parse = TRUE) +
  theme_bw(base_size = 16)

### bonus: including result table
ggplot(data = df, aes(x = x, y = y)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, formula = formula1) +
  stat_fit_tb(method = "lm",
              method.args = list(formula = formula1),
              tb.vars = c(Parameter = "term", 
                          Estimate = "estimate", 
                          "s.e." = "std.error", 
                          "italic(t)" = "statistic", 
                          "italic(P)" = "p.value"),
              label.y = "bottom", label.x = "right",
              parse = TRUE) +
  stat_poly_eq(aes(label = paste0("atop(", ..eq.label.., ",", ..rr.label.., ")")), 
               formula = formula1, 
               parse = TRUE) +
  theme_bw(base_size = 16)

^{Created by the reprex package (v0.3.0)}