Display the result of a linear model and its confidence interval on top of a scatterplot. A ggplot2 implementation with reproducible code.
Adding a linear trend to a
scatterplot helps the reader in seeing
patterns. ggplot2
provides the
geom_smooth()
function that allows to add the linear trend
and the confidence interval around it if needed (option
se=TRUE
).
Note:: the method
argument allows to apply different
smoothing method like glm, loess and more. See the
doc
for more.
# Library
library(ggplot2)
library(hrbrthemes)
# Create dummy data
data <- data.frame(
cond = rep(c("condition_1", "condition_2"), each=10),
my_x = 1:100 + rnorm(100,sd=9),
my_y = 1:100 + rnorm(100,sd=16)
)
# Basic scatter plot.
p1 <- ggplot(data, aes(x=my_x, y=my_y)) +
geom_point( color="#69b3a2") +
theme_ipsum()
# with linear trend
p2 <- ggplot(data, aes(x=my_x, y=my_y)) +
geom_point() +
geom_smooth(method=lm , color="red", se=FALSE) +
theme_ipsum()
# linear trend + confidence interval
p3 <- ggplot(data, aes(x=my_x, y=my_y)) +
geom_point() +
geom_smooth(method=lm , color="red", fill="#69b3a2", se=TRUE) +
theme_ipsum()