How to decide which factor to confound in 2^5 factorial design?

26 June 2020 0 7K Report

I am designing a 2^5 factorial design (5 factors, each at 2 levels). This would yield 32 treatment combinations that I want to distribute among 8 blocks (4 experiments per block) and 3 replications. Attached is the design matrix with randomly distributed treatments. Could anyone please help me with better design approach, and how to use confounding here?

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