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We need to assign the two additional factors (F and G) to interactions of the basic factors. We typically choose high-order interactions to minimize aliasing.
Because ABC is confounded with blocks, the block effect is not separable from ABC. But we can still compute other effects using the contrast method .
(A = (-1, +1, -1, +1, -1, +1, -1, +1) ) (B = (-1, -1, +1, +1, -1, -1, +1, +1)) (C = (-1, -1, -1, -1, +1, +1, +1, +1))
Main effects B and C are large (5.75, 4.25). AB interaction is modest (1.75). Note: We do not compute ABC because it’s confounded with blocks.
for a random main effect when an interaction exists will lead to a Type I error (finding significance where there is none). 5. Software Implementation Most solutions in this chapter are best handled using:
Block 1 total = 25+30+28+32 = 115 Block 2 total = 22+20+24+35 = 101 Difference = 14. Yes — exactly the ABC contrast. Thus ABC is completely confounded.
We need to assign the two additional factors (F and G) to interactions of the basic factors. We typically choose high-order interactions to minimize aliasing.
Because ABC is confounded with blocks, the block effect is not separable from ABC. But we can still compute other effects using the contrast method .
(A = (-1, +1, -1, +1, -1, +1, -1, +1) ) (B = (-1, -1, +1, +1, -1, -1, +1, +1)) (C = (-1, -1, -1, -1, +1, +1, +1, +1))
Main effects B and C are large (5.75, 4.25). AB interaction is modest (1.75). Note: We do not compute ABC because it’s confounded with blocks.
for a random main effect when an interaction exists will lead to a Type I error (finding significance where there is none). 5. Software Implementation Most solutions in this chapter are best handled using:
Block 1 total = 25+30+28+32 = 115 Block 2 total = 22+20+24+35 = 101 Difference = 14. Yes — exactly the ABC contrast. Thus ABC is completely confounded.
