Perhaps beyond the scope of your question, but the factors that affect design selection are:
- Constraints: Time, money, measurement capability, etc. How many treatments can be made?
- How many factors are to be manipulated (the number of hypotheses to be compared)?
- How will noise be managed or partitioned?
- Are some factors harder to change than others? Are there other restrictions on randomization?
- Are interactions (or other higher order effects) suspected/predicted?
- What is the desired resolution? (What effects do you want to estimate/separate?)
"All models are wrong, some are useful" G.E.P. Box
