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Testing do(x) Claims

When X is non-manipulable, although direct tests of Q(x) are infeasible, indirect tests are available.We can use back-door adjustment or front-door adjustment to test Q.

For example, if a set of variable z satisfies the back door criterion relative to (X,Y), Q(x) is identifiable and is given by the formula: P(ydo(x))=zP(yx,z)P(z) P(y|do(x))=\sum_{z} P(y|x,z)P(z). Equating the adjustment formulae generated by each of those sets provides a test for M, and hence a test for Q.

Fig.1 shows a front-door model where I is manipulable, X is non-manipulable, and U is an unobserved confounder. X satisfies the front door criterion relative to (I,Y). Randomizing I yields an estimate of P(y|do(I)), which should be equal to the estimand of P(y|do(I)) obtained through the front-door formula. The causal effect of I on Y is identifiable and is given by the formula: Q(x)=iP(yx,I=i)P(I=i)Q(x)=\sum_{i} P(y|x, I = i)P(I = i)

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Updated 2020-04-19

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Data Science