Krahasoni metodat
Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.
| Analiza Bayesiane Kaplan-Meier× | Analiza Kaplan-Meier× | |
|---|---|---|
| Fusha | Epidemiologji | Epidemiologji |
| Familja | Process / pipeline | Process / pipeline |
| Viti i origjinës≠ | 1976 | 1958 |
| Krijuesi≠ | Susarla & Van Ryzin (Bayesian nonparametric survival estimation) | Edward L. Kaplan and Paul Meier |
| Lloji≠ | Bayesian nonparametric survival analysis | Nonparametric survival estimator |
| Burimi themelues≠ | Susarla, V., & Van Ryzin, J. (1976). Nonparametric Bayesian estimation of survival curves from incomplete observations. Journal of the American Statistical Association, 71(356), 897–902. DOI ↗ | Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗ |
| Emërtime të tjera | Bayesian survival curve estimation, Bayesian nonparametric survival analysis, Dirichlet process Kaplan-Meier, BKM | KM analysis, KM estimator, product-limit estimator, Kaplan-Meier curve |
| Të lidhura≠ | 4 | 5 |
| Përmbledhja≠ | Bayesian Kaplan-Meier analysis extends the classical Kaplan-Meier estimator by placing a prior distribution over the survival function and updating it with observed time-to-event data to obtain a full posterior distribution for the survival curve. This approach, rooted in Susarla and Van Ryzin's 1976 Dirichlet-process framework, yields credible intervals rather than confidence intervals and enables coherent incorporation of prior clinical knowledge, making it particularly valuable in small-sample or early-phase clinical settings. | 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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