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The IDAG allows for a both intuitive and stringent way of illustrating interactions. It helps to distinguish between causal and non-causal mechanisms behind effect variation. Conclusions about how to empirically estimate interactions can be drawn-as well as conclusions about how to achieve generalizability in contexts where interest lies in estimating an overall effect.
Nilsson et al. (Tue,) studied this question.