CODEWITHSUNDEEP
rggplot2
lukeg
lukeg

Reputation: 1357

multiple log regression models ggplot2

In the following example, I follow on from the following link, in which we learn the basic to creating a log regression model.

data(mtcars)
dat <- subset(mtcars, select=c(mpg, am, vs))
logr_vm <- glm(vs ~ mpg, data=dat, family=binomial)
library(ggplot2)
ggplot(dat, aes(x=mpg, y=vs)) + geom_point() + 
  stat_smooth(method="glm", method.args=list(family="binomial"), se=T) + 
  theme_bw()

Now I want to create a second log model where we predict a new outcome vs2. How can I use ggplot2 to show the two models with different colours?

dat$vs2 <- with(dat, ifelse(mpg > 20, 1, vs))

so that the secondary log model is ....

logr_vm2 <- glm(vs2 ~ mpg, data=dat, family=binomial)

Upvotes: 0

Views: 391

Answers (1)

Axeman
Axeman

Reputation: 35307

When fitting the models with ggplot itself, and you only have a few models, you can easily add a legend by manually mapping a model name to colors inside aes. The rest will then be taken care of.

Addionally, I use geom_count instead of geom_point to show that we have overlapping values here, and add some colors to show your different categories:

ggplot(dat, aes(x = mpg)) + 
  geom_count(aes(y = vs, col = mpg > 20), alpha = 0.3) + 
  stat_smooth(aes(y = vs, fill = 'm1'), col = 'black',
              method = "glm", method.args = list(family = "binomial")) + 
  stat_smooth(aes(y = vs2, fill = 'm2'), col = 'black', 
              method = "glm", method.args = list(family = "binomial")) +
  scale_size_area() +
  scale_color_discrete(h.start = 90) +
  theme_bw()

enter image description here

Upvotes: 4

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