We're piloting a multiple variable testing program at my company. For starters, we're looking at a test with 3 factors (a, b, c), 2 levels (-1,+1) each. Based on research from several standard texts, we picked the test cells as
The generator is c=ab and defining relation is I=abc
How the balanced fractional design above different from just having a control (-1), and 3 test cells a, b, c? If in the design above all 2nd and 3rd order interactions are confounded with main effects, then what do we gain from it information-wise vs. the simpler design that just tests the main effects individually?
What are some techniques to analyze the results? The answer that we ultimately want to get to is- what is the optimal combination of factors a, b and to maximize the response variable y?