So sánh phương pháp
Xem các phương pháp đã chọn cạnh nhau; những hàng khác biệt được làm nổi bật.
| Mô hình Cấu trúc Biên về Hiệu quả Điều trị Không đồng nhất (HTE-MSM)× | Trọng số điểm xu hướng (PSW / IPW)× | |
|---|---|---|
| Lĩnh vực | Suy luận nhân quả | Suy luận nhân quả |
| Họ | Regression model | Regression model |
| Năm ra đời≠ | 2000–2010s | 1983 (propensity score); 2003 (efficient IPW estimator) |
| Người khởi xướng≠ | Robins, Hernan & Brumback (foundational MSM framework, 2000); heterogeneous-effect extensions developed throughout 2000s–2010s | Rosenbaum & Rubin (propensity score); Hirano, Imbens & Ridder (efficient weighting) |
| Loại≠ | Causal inference / weighted regression with effect modification | Causal inference / reweighting |
| Công trình gốc≠ | Robins, J. M., Hernan, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550-560. DOI ↗ | Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41-55. DOI ↗ |
| Tên gọi khác | HTE-MSM, heterogeneous MSM, subgroup MSM, effect-modified marginal structural model | PSW, inverse probability weighting, IPW, propensity-based weighting |
| Liên quan≠ | 5 | 6 |
| Tóm tắt≠ | 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. | Propensity score weighting is a causal-inference method that reweights observations so that the covariate distributions of treated and untreated units look exchangeable, enabling unbiased estimation of average treatment effects from observational data. Each unit receives a weight that is the inverse of its probability of receiving the treatment it actually received — a strategy formalised by Rosenbaum and Rubin (1983) and given its efficient semiparametric form by Hirano, Imbens and Ridder (2003). |
| ScholarGateBộ dữ liệu ↗ |
|
|