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Guanglei Hong; Fan Yang; Xu Qin – Grantee Submission, 2023
In causal mediation studies that decompose an average treatment effect into indirect and direct effects, examples of post-treatment confounding are abundant. In the presence of treatment-by-mediator interactions, past research has generally considered it infeasible to adjust for a post-treatment confounder of the mediator-outcome relationship due…
Descriptors: Causal Models, Mediation Theory, Research Problems, Statistical Inference
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Xu Qin – Grantee Submission, 2023
When designing a study for causal mediation analysis, it is crucial to conduct a power analysis to determine the sample size required to detect the causal mediation effects with sufficient power. However, the development of power analysis methods for causal mediation analysis has lagged far behind. To fill the knowledge gap, I proposed a…
Descriptors: Sample Size, Statistical Analysis, Causal Models, Mediation Theory