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Published on: July 3, 2020
Marginal structural models for estimating principal stratum direct effects under the monotonicity assumption
1Division of Biostatistics, Clinical Research Center, Kinki University School of Medicine 377-2, Ohno-higashi, Osakasayama, Osaka 589-8511, Japan. chibay@med.kindai.ac.jp
This study introduces marginal structural models (MSMs) to estimate principal stratum direct effects (PSDEs), which represent causal effects within specific subgroups. These models offer a method for calculating direct treatment effects when mediators remain constant.
Area of Science:
- Epidemiology
- Biostatistics
- Causal Inference
Background:
- Estimating direct treatment effects, unmediated by intermediate variables, is crucial in clinical and epidemiological research.
- Previous methods, like VanderWeele's 2009 marginal structural models (MSMs), focused on mediator interventions.
- Principal stratification offers an alternative framework for defining direct effects within latent subgroups.
Purpose of the Study:
- To propose marginal structural models (MSMs) for estimating principal stratum direct effects (PSDEs).
- To provide a method for assessing causal effects within latent subgroups where the mediator is constant, irrespective of exposure.
Main Methods:
- Development of marginal structural models (MSMs) tailored for principal stratum direct effects (PSDEs).
- Utilizing the principal stratification framework to define latent subgroups based on mediator constancy.
- Application of MSMs under the assumption of monotonicity.
Main Results:
- Demonstration that PSDEs can be readily estimated using the proposed MSMs.
- Validation of the MSM approach for causal effect estimation within principal strata.
Conclusions:
- Marginal structural models (MSMs) provide a feasible approach for estimating principal stratum direct effects (PSDEs).
- The monotonicity assumption facilitates the estimation of direct effects within principal strata using MSMs.
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