The Identification of Direct and Indirect Effects in Studies with an Unmeasured Intermediate Variable

This paper considers the identification problem of direct and indirect effects of treatment on a response, when observed data are available but an important intermediate variable is unmeasured. To solve this problem, we propose identification conditions for direct and indirect effects based on (conditionally independent) proxy variables of the unmeasured intermediate variable. This paper establishes feasible approaches for evaluating direct and indirect effects in studies with a single unmeasured intermediate variable.