CODEWITHSUNDEEP
rggplot2glm
Aaron Stone
Aaron Stone

Reputation: 31

Adding predict line from glm to ggplot2, larger than original data set

I have included a sample data set just to demonstrate what I am trying to do. 

Speed <- c(400,220,490,210,500,270,200,470,480,310,240,490,420,330,280,210,300,470,230,430,460,220,250,200,390)

Hit <- c(0,1,0,1,0,0,1,0,0,1,1,0,0,1,1,1,1,1,0,0,0,1,1,1,0)

obs <- c(1:25)

msl2.data <- as.data.frame(cbind(obs,Hit,Speed))

msl2.glm <- glm(Hit ~ Speed, data = msl2.data, family = binomial)

Doing What I want in the base package. 

plot(Hit~ Speed, data = msl2.data, xlim = c(0,700), xlab = "Speed", ylab = "Hit", main = "Plot of hit vs Speed")

pi.hat<-(predict( msl2.glm, data.frame(Speed=c(0:700)), type="response" ))

lines( 0:700, pi.hat, col="blue" )

I am trying to recreate the above plot, but in ggplot. The error I have been unable to work around is the aes(x,y) have different lengths, which is true, but I want them to have different lengths.

Any ideas for this in gg?

Upvotes: 3

Views: 5626

Answers (1)

user20650
user20650

Reputation: 25914

You have a couple of approaches; the first does all the modelling inside of ggplot, the second does it outside and passes the relevant data to be plot.

First

gplot(dat=msl2.data, aes(Speed, Hit)) + 
      geom_point() +
      geom_smooth(method="glm", method.args=list(family="binomial"), 
                  fullrange=TRUE, se=FALSE) +
      xlim(0, 700)

fullrange is specified so the prediction lines covers the x-range. xlim extends the x-axis.

Second

#Create prediction dataframe
pred <- data.frame(Speed=0:700, pi.hat)

ggplot() + 
  # prediction line
  geom_line(data=pred, aes(Speed, pi.hat)) +
  # points - note different dataframe is used
  geom_point(dat=msl2.data, aes(Speed, Hit))

I generally prefer to do the modelling outside (second approach), and use ggplot purely as a plotting mechanism.

Upvotes: 6

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