I have two data sets that include variables regarding consumers website usage and click behavior on display ads. The click response per session can only be 1 (clicked) or 0 (not clicked), since only the first reaction within a session was measured. The data are available for several user sessions and would look something like this:
Session_1 Session_2 Session_3 Session_n
Impressions_Banner_1 2 4 1 [...]
Impressions_Banner_2 1 6 1 [...]
Click_Response_Banner_1 1 0 0 [...]
Click_Response_Banner_2 0 1 0 [...]
Page_Views 2 5 3 [...]
Visit_Duration 31 121 60 [...]
I would like to test if it is appropriate to pool the data and combine the variables for banner 1 and banner 2. The question is, how do I test for homogeneity?
The final goal is to run an logistic regression to analyze if/how consumers' website usage behavior has an significant influence on their ad response.