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Marginal Structural Model/Evidence
Method evidence record

Marginal Structural Model

A marginal structural model is a causal modeling framework designed to estimate the effect of a time-varying treatment in the presence of time-varying confounders that are themselves affected by prior treatment. By reweighting observations with inverse probability of treatment weights, MSMs create a pseudo-population in which confounding is eliminated, enabling unbiased estimation of causal treatment contrasts even when standard regression adjustments would fail.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Marginal Structural Model with Inverse Probability of Treatment Weighting
Taxonomic method record · regression-model / causal-inference
  • 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
  • Hernan, M. A., & Robins, J. M. (2020). Causal Inference: What If. Chapman & Hall/CRC. · URL
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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Same method familyDifference-in-Differencesmachine-suggested · Relational suggestion, not evidence.Same method familyDoubly Robust Estimationmachine-suggested · Relational suggestion, not evidence.Same method familyG-Computationmachine-suggested · Relational suggestion, not evidence.Same method familyInverse Probability Weightingmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketPropensity Score Weightingmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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