Concept

Apply CDE to Berkeley Admissions Paradox

We would like to examine the direct effect of XX on YY without allowing MM to change. In the context of the Berkeley example, X represents the gender, Y represents the admission result, M represents the mediator(department candidates apply to). We force everybody to apply to the history department by setting do(M=0)do(M = 0). People are randomly asked to report their sex as male (do(X=1)do(X = 1)) or as female (do(X=0)do(X = 0)), regardless of their actual genders. We obtain CDE through the difference in admission rates between the two groups. In symbols, CDE(0)CDE(0) indicates that we forced the mediator to take on the value zero, i.e. the history department. We could also force everybody to apply to the engineering department: do(M=1)do(M = 1). We would then denote the resulting controlled direct effect as CDE(1)CDE(1).

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Updated 2020-04-12

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Data Science