Bayesian inference for the causal effect of mediation
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Updated: May 18, 2026

Problem-Solving Before Instruction (PS-I): A Protocol for Assessment and Intervention in Students with Different Abilities
Published on: September 11, 2021
Michael J Daniels1, Jason A Roy, Chanmin Kim
1Department of Statistics, University of Florida, Gainesville, FL 32611, USA. mdaniels@stat.ufl.edu
Abstract:
We propose a nonparametric Bayesian approach to estimate the natural direct and indirect effects through a mediator in the setting of a continuous mediator and a binary response. Several conditional independence assumptions are introduced (with corresponding sensitivity parameters) to make these effects identifiable from the observed data. We suggest strategies for eliciting sensitivity parameters and conduct simulations to assess violations to the assumptions. This approach is used to assess mediation in a recent weight management clinical trial.
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