Mediation analysis for count and zero-inflated count data without sequential ignorability and its application in dental studies.

ABSTRACT: Mediation analysis seeks to understand the mechanism by which a treatment affects an outcome. Count or zero-inflated count outcomes are common in many studies in which mediation analysis is of interest. For example, in dental studies, outcomes such as the number of decayed, missing and filled teeth are typically zero inflated. Existing mediation analysis approaches for count data often assume sequential ignorability of the mediator. This is often not plausible because the mediator is not randomized so unmeasured confounders are associated with the mediator and the outcome. We develop causal methods based on instrumental variable approaches for mediation analysis for count data possibly with many 0s that do not require the assumption of sequential ignorability. We first define the direct an

SUBMITTER: Guo Z 

PROVIDER: S-EPMC6457264 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature