方法对比
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| 风险调整的Kaplan-Meier分析× | 逆概率治疗加权法 (IPW / IPTW)× | |
|---|---|---|
| 领域≠ | 流行病学 | 因果推断 |
| 方法族≠ | Process / pipeline | Regression model |
| 起源年份≠ | 2001–2004 (formal statistical framework for weighted KM curves) | 2000 |
| 提出者≠ | Conceptual basis: Kaplan & Meier (1958); risk-adjustment via IPTW formalised by Hernán, Brumback & Robins (2001), with practical implementation by Cole & Hernán (2004) | Robins, Hernán & Brumback |
| 类型≠ | Adjusted non-parametric survival method | Causal inference weighting estimator |
| 开创性文献≠ | Cole, S. R., & Hernan, M. A. (2004). Adjusted survival curves with inverse probability weights. Computer Methods and Programs in Biomedicine, 75(1), 45–49. DOI ↗ | Robins, J. M., Hernán, M. A., & Brumback, B. (2000). Marginal Structural Models and Causal Inference in Epidemiology. Epidemiology, 11(5), 550-560. DOI ↗ |
| 别名≠ | weighted Kaplan-Meier, IPTW-adjusted Kaplan-Meier, propensity-score-weighted survival curves, adjusted survival curves | IPW, IPTW, inverse probability of treatment weighting, marginal structural model weighting |
| 相关 | 5 | 5 |
| 摘要≠ | Risk-adjusted Kaplan-Meier analysis combines the non-parametric Kaplan-Meier estimator with inverse probability of treatment weighting (IPTW) or similar risk-adjustment procedures to produce survival curves that are comparable across groups as if the groups had identical distributions of baseline confounders. It is the observational-study analogue of plotting survival curves from a randomised trial. | 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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