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Heterogeneous Treatment Effect Marginal Structural Model/Evidence
Method evidence record

Heterogeneous Treatment Effect Marginal Structural Model

The Heterogeneous Treatment Effect Marginal Structural Model extends the classic MSM framework of Robins, Hernan, and Brumback to estimate how treatment effects vary across subgroups or individual-level moderators. By weighting observations with inverse probability of treatment weights (IPTW) and interacting the treatment with effect modifiers in the weighted outcome model, the approach produces subgroup-specific or continuous causal effect estimates from observational data.

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Source record

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

Heterogeneous Treatment Effect Marginal Structural Model
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 familyDoubly Robust Estimationmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketHeterogeneous Treatment Effect Difference-in-Differencesmachine-suggested · Relational suggestion, not evidence.Same method familyInverse Probability Weightingmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMarginal Structural Modelmachine-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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