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The micro-randomized trial (MRT) is a sequential randomized experimentaldesign to empirically evaluate the effectiveness of mobile health (mHealth)intervention components that may be delivered at hundreds or thousands ofdecision points. MRTs have motivated a new class of causal estimands, termed"causal excursion effects", for which semiparametric inference can be conductedvia a weighted, centered least squares criterion (Boruvka et al., 2018).Existing methods assume between-subject independence and non-interference.Deviations from these assumptions often occur. In this paper, causal excursioneffects are revisited under potential cluster-level treatment effectheterogeneity and interference, where the treatment effect of interest maydepend on cluster-level moderators. Utility of the proposed methods is shown byanalyzing data from a multi-institution cohort of first year medical residentsin the United States.

Assessing Time-Varying Causal Effect Moderation in the Presence of Cluster-Level Treatment Effect Heterogeneity