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measuring impacts on rare outcomes

Statistical Power and the Funnel of Attribution

David McKenzie's picture

Often there are many steps or stages between the starting point of some intervention and its ultimate goal, and at each step, people can drop out. The result can be extremely low power to measure impacts on this end outcome, even though we might be able to detect impacts on the intermediate steps. This post illustrates this point, with the goal of making clear the importance of trying to measure intermediate outcomes, and concludes with suggestions of ways to partially overcome this problem.