Primary Submission Category: Generalizability/Transportability
Disparate effect of missing mediators on the transportability of causal effects
Authors: Vishwali Mhasawade, Vishwali Mhasawade, Rumi Chunara,
Presenting Author: Vishwali Mhasawade*
Transported mediation effects provide an avenue to understand how upstream interventions, as opposed to proximal interventions, such as individual behaviors, would work differently when applied to different populations. However, when mediators are missing in the populations where the effect is to be transported, these estimates could be biased, with the conditional average treatment effect being insignificant for the subgroup with missing mediator data. We study this issue of missing mediators, motivated by challenges in public health where the mediators are commonly missing, not at random. We propose a sensitivity analysis framework that quantifies the impact of missing mediator data on transported mediation effects. This framework enables us to identify the settings under which the conditional transported mediation effect is rendered insignificant for the subgroup with missing mediator data. Specifically, we provide the bounds on the transported mediation effect as a function of missingness. We then apply the sensitivity framework to longitudinal data from the Moving to Opportunity Study, a large-scale housing voucher experiment, to transport effect estimates of voucher receipt, an upstream intervention on living location, in childhood on subsequent risk of mental health or substance use disorder mediated through parental health across sites. Our findings contribute to a tangible understanding of how much missing data can be withstood for unbiased effect estimates.