Comment: Clarifying Endogeneous Data Structures and Consequent Modelling Choices Using Causal Graphs

We read with great interest the article by Qian, Klasnja and Murphy (2019), and commend them for focusing on principled estimation and a quantitative focus on healthcare delivery through mobile devices. The quantitative analyses studied here could have wide-ranging applications that may serve to increase patient empowerment by taking medical monitoring and even intervention out of the clinic and into the home. Here we wish to delve into two complementary aspects of the work: first, we attempt to give clarifications concerning the parameter(s) of interest, and secondly, we provide visualizations of potential scenarios that may help to clarify estimands and when biases due to endogeneity may arise.