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A test for the correct specification of marginal structural models.

Alioune Sall1,2, Karine Aubé2, Xavier Trudel2,3

  • 1Département de Mathématiques et de Statistique, Université Laval, Québec City, Canada.

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|March 12, 2019
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Marginal structural models (MSMs) can estimate causal effects with time-varying factors. This study introduces a new test to validate MSM assumptions, ensuring reliable causal inference in observational studies.

Keywords:
causal inferencemarginal structural modelsmodel specification

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Area of Science:

  • Epidemiology
  • Biostatistics
  • Causal Inference

Background:

  • Marginal structural models (MSMs) are used for causal inference with time-varying exposures and confounders.
  • Estimating MSM parameters relies on correct model specification, which is often unknown in practice.

Purpose of the Study:

  • To propose and validate a statistical test for assessing the correct specification of marginal structural models.
  • To evaluate the performance of the proposed model specification test via simulation.

Main Methods:

  • Development of a novel statistical test for marginal structural model (MSM) specification.
  • Inverse probability of treatment weighting (IPTW) for parameter estimation.
  • Simulation studies to assess test performance.
  • Application to a real-world cohort study.

Main Results:

  • The proposed test effectively validates the correct specification assumption for MSMs.
  • Simulation results demonstrate the test's performance characteristics.
  • The approach was successfully applied to analyze the impact of psychosocial stressors on blood pressure.

Conclusions:

  • The developed test provides a valuable tool for validating marginal structural models.
  • This facilitates more reliable causal effect estimation in the presence of time-dependent confounding.
  • The methodology is applicable to various observational health studies.