Main effect of factor A: ME(A) = z̄(A+) − z̄(A−), where z̄(A+) is the average of the zi values observed at A+ and z̄(A−) is similarly defined. Interaction effect between factors A and B: INT(A, B) = 1...


Main effect of factor A: ME(A) = z̄(A+) − z̄(A−), where z̄(A+) is the average


of the zi values observed at A+ and z̄(A−) is similarly defined. Interaction effect


between factors A and B:


INT(A, B) = 1


2


[ME(B|A+) − ME(B|A−)]


= 1


2


[ME(A|B+) − ME(A|B−)]


= 1


2


{z̄(A + |B+) + z̄(A − |B−)}


− 1


2


{z̄(A + |B−) + z̄(A − |B+)},


where ME(B|A+) = z̄(B + |A+) − z̄(B − |A+) is the conditional main effect of


factor B at the + level of factor A, and other ME terms can be similarly defined.


A significant interaction between A and B suggests that the effect of one factor


depends on the level of the other factor. For k factors define their interaction


in terms of the (k − 1)-factor interactions:


INT(A1, A2, ..., Ak) = 1


2


INT(A1, A2, ..., Ak−1|Ak+)


− 1


2


INT(A1, A2, ..., Ak−1|Ak−),


which can be written as z̄+ − z̄−, where z̄+ is the average of the z values at


the factorial combinations whose product of its levels is +; z̄− is similarly


defined. These factorial effects can be estimated via regression analysis by


using a model like (4.15).



May 26, 2022
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