Regression modelQuasi-experimental / causal inference

Panel Data Marginal Structural Model (MSM)

A panel data marginal structural model (MSM) uses inverse probability of treatment weighting (IPTW) across multiple time periods to estimate the causal effect of a time-varying treatment, while appropriately adjusting for time-varying confounders that are themselves affected by prior treatment — a bias source that conventional regression cannot handle.

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Sources

  1. Robins, J. M., Hernan, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550-560. DOI: 10.1097/00001648-200009000-00011
  2. Hernan, M. A., & Robins, J. M. (2020). Causal Inference: What If. Chapman & Hall/CRC. link

Related methods

Referenced by

ScholarGatePanel Data Marginal Structural Model (Panel Data Marginal Structural Model with Inverse Probability Weighting). Retrieved 2026-06-04 from https://scholargate.app/en/causal-inference/panel-data-marginal-structural-model