Path-specific causal decomposition analysis with multiple correlated mediator variables.

ABSTRACT: A causal decomposition analysis allows researchers to determine whether the difference in a health outcome between two groups can be attributed to a difference in each group's distribution of one or more modifiable mediator variables. With this knowledge, researchers and policymakers can focus on designing interventions that target these mediator variables. Existing methods for causal decomposition analysis either focus on one mediator variable or assume that each mediator variable is conditionally independent given the group label and the mediator-outcome confounders. In this article, we propose a flexible causal decomposition analysis method that can accommodate multiple correlated and interacting mediator variables, which are frequently seen in studies of health behaviors and studies of

SUBMITTER: Smith MJ 

PROVIDER: S-EPMC11570347 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature