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| Trọng số xác suất nghịch đảo đa kỳ× | Trọng số Xác suất Nghịch đảo của Điều trị (IPW / IPTW)× | |
|---|---|---|
| Lĩnh vực | Suy luận nhân quả | Suy luận nhân quả |
| Họ | Regression model | Regression model |
| Năm ra đời | 2000 | 2000 |
| Người khởi xướng≠ | Robins, Hernan & Brumback | Robins, Hernán & Brumback |
| Loại≠ | Weighted causal estimator | Causal inference weighting estimator |
| 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 ↗ | Robins, J. M., Hernán, M. A., & Brumback, B. (2000). Marginal Structural Models and Causal Inference in Epidemiology. Epidemiology, 11(5), 550-560. DOI ↗ |
| Tên gọi khác≠ | longitudinal IPW, multi-period IPW, time-varying IPW, sequential IPW | IPW, IPTW, inverse probability of treatment weighting, marginal structural model weighting |
| Liên quan≠ | 6 | 5 |
| Tóm tắt≠ | Multi-period Inverse Probability Weighting (IPW) estimates the causal effect of a treatment that varies across multiple time periods by reweighting observations according to the probability of receiving each period's treatment given past treatment history and time-varying confounders. It creates a pseudo-population where treatment at each period is independent of measured confounders, enabling unbiased estimation of sustained treatment strategies. | Inverse Probability Weighting is a causal-inference method that assigns each observation a weight equal to the inverse of its probability of receiving the treatment it actually received. Introduced by Robins, Hernán and Brumback (2000) for marginal structural models, it builds a pseudo-population in which treatment is independent of measured confounders, balancing selection bias. |
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