Hi, I’m working on a dataset collected from a 2-way Anova design (kind of) on binary data. The purpose of the experiment is to explore how different types of email marketing incentives affect customers propensity to buy certain fruits. The dependent variable is Purchase rate (Binary; if a customer purchased the offered fruit or not) Factor A has 3 Levels: 1. Silent Communication (No incentive offered. To observe customers natural propensity to buy any given fruit.) 2. Email explaining the benefits of consuming the fruit being offered 3. Same as 2 but with a 15% discount on the fruit offered Factor B has 5 levels. Customers in these groups are incentivized to consume: 1. Bananas 2. Apples 3. Oranges 4. Kiwis 5. Fruit of choice (Of the 4 above) A sample of 150 000 subscribers were randomly allocated to one of the 15 groups with 10k subscribers in each group. The questions I have are the following: - Which method or technique should I use to account for the binary response variable? - When testing the main effect for Factor B, I do not want to test the difference in purchase rates shown in Table 1 (which is what is computed by default in SAS?). Rather, I’m interested in comparing the differences in purchase rate uplifts between the groups, i.e. the numbers in table 2 highlighted in green. I would appreciate to get some guidance and advise on how to handle the two issues described?
... View more