Effect plots
One way to better understand the marginal effect of a unit change in price ratio is to use the logistic response model with some typical values and graph the predictions.
You can do this by using the function cplot()
from the margins
package. The function cplot()
takes on the logistic.model
object, the name of the predictor variable and the corresponding typical values as arguments. You assume the typical values for price.ratio
to be in the range from -2
to 2
. As you only want to investigate the predictions for a few values you define a sequence of numbers from -2
to 2
with increments 0.50
by using the function seq()
.
This exercise is part of the course
Building Response Models in R
Exercise instructions
- Define a sequence of numbers ranging from
-2
to2
and having increments0.50
by using the functionseq()
. Assign the result to an object namedx
. - Plot the predicted purchase probabilities given
"price.ratio"
andx
by using the functioncplot()
.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Define the sequence of x values
x <- seq(from = ___, to = ___, by = ___)
# Plot the price.ratio effect
___(logistic.model, ___, xvals = ___)