Exact parametric causal mediation analysis for non-rare binary outcomes with binary mediators
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In this paper, we derive the exact parametric expressions of natural direct and indirect effects, on the odds-ratio scale, in settings with a binary mediator. The effect decomposition we propose does not require the outcome to be rare and generalizes the existing one, allowing for interactions between both the exposure and the mediator and confounding covariates. Further, it outlines a more interpretable relationship between the causal effects and the correspondent pathway-specific logistic regression parameters. Our findings are applied to data coming from a microfinance experiment performed in Bosnia and Herzegovina. A simulation study for a comparison with estimators relying on the rare outcome assumption is also implemented.
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