Marketing example
As described in the video, our client is interested in knowing if a friend's recommendation increases the number of people who buy, rather than pass, on his online product. He has given us a summary of his data as a data.frame
called all_data
. This data includes the number of Purchases
and Pass
es for 4 test cities (city
) as well as the customer ranking
. This data structure lends itself to using cbind()
on the two columns of interest to create a matrix (You could use other methods of making a matrix in R, but this is one of the easiest methods).
You are interested to see if the recommendation from a friend
increases people buying the product. To answer this question, you will build a glmer()
model and then examine the model's output.
If the parameter estimate for friend
is significantly greater than zero, then a friend's recommendation increases the chance somebody makes a purchase.
If the parameter estimate for friend
is significantly less than zero, then a friend's recommendation decreases the chance somebody makes a purchase.
If the parameter estimate for friend
is not significantly different than zero, then a friend's recommendation has no effect on somebody making a purchase.
This exercise is part of the course
Hierarchical and Mixed Effects Models in R
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Load lmerTest
library(lmerTest)
# Fit the model and look at its summary
model_out <- ___
summary(model_out)