Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Jaudas analīze izdzīvošanas pētījumiem× | Kaplana-Meiera izdzīvošanas novērtētājs× | |
|---|---|---|
| Nozare≠ | Statistika | Dzīvildze |
| Saime≠ | Hypothesis test | Survival analysis |
| Izcelsmes gads≠ | 1981 | 1958 |
| Autors≠ | — | Kaplan, E. L. & Meier, P. |
| Tips≠ | Sample size determination for survival outcomes | Non-parametric survival estimator |
| Pirmavots≠ | Schoenfeld, D. A. (1981). The asymptotic properties of nonparametric tests for comparing survival distributions. Biometrika, 68(1), 316–319. DOI ↗ | Kaplan, E. L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗ |
| Citi nosaukumi≠ | log-rank power analysis, cox regression power analysis, survival power analysis, Sağkalım Analizi Güç Analizi | product-limit estimator, km curve, kaplan-meier sağkalım analizi |
| Saistītās≠ | 6 | 2 |
| Kopsavilkums≠ | Power analysis for survival studies determines how many participants — and how many observed events — are required so that a log-rank test or Cox regression has a sufficient probability of detecting a clinically meaningful difference in survival between groups. The foundational formulas were derived by Schoenfeld (1981) and Lachin (1981) and remain the standard approach in clinical trial planning. | The Kaplan-Meier estimator, introduced by Kaplan and Meier in 1958, is a non-parametric method that estimates the survival curve — the probability of remaining event-free over time — from right-censored time-to-event data. The log-rank test is the companion procedure used to compare survival curves between groups. |
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