方法对比
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| 匹配的Kaplan-Meier分析× | Kaplan-Meier分析× | |
|---|---|---|
| 领域 | 流行病学 | 流行病学 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1958 (KM); matched application formalized 1980s–2000s | 1958 |
| 提出者≠ | Kaplan & Meier (KM method, 1958); matching extensions developed through propensity score methods (Rosenbaum & Rubin, 1983) | Edward L. Kaplan and Paul Meier |
| 类型≠ | Nonparametric survival analysis with observational confounder control | Nonparametric survival estimator |
| 开创性文献≠ | Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457-481. DOI ↗ | Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗ |
| 别名 | KM analysis in matched cohorts, propensity-matched survival curves, matched survival analysis, paired Kaplan-Meier | KM analysis, KM estimator, product-limit estimator, Kaplan-Meier curve |
| 相关≠ | 6 | 5 |
| 摘要≠ | Matched Kaplan-Meier analysis estimates and compares survival functions in groups that have been pre-balanced through individual or propensity-score matching. By applying the Kaplan-Meier product-limit estimator to matched cohorts or matched pairs, investigators can visualize time-to-event outcomes while controlling for confounders that would otherwise distort treatment or exposure comparisons in observational data. | Kaplan-Meier (KM) analysis is a nonparametric method for estimating the survival function from time-to-event data. Introduced by Kaplan and Meier in 1958, it produces the classic step-function survival curve that shows the probability of surviving beyond each observed event time, correctly accounting for censored observations — participants who left the study or had not yet experienced the event by the end of follow-up. It is one of the most widely used techniques in clinical and epidemiological research. |
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