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| Styrkeberegning for overlevelsesstudier× | Poweranalyse for proportions-tests× | |
|---|---|---|
| Fagområde | Statistik | Statistik |
| Familie | Hypothesis test | Hypothesis test |
| Oprindelsesår≠ | 1981 | 1988 |
| Ophavsperson≠ | — | Jacob Cohen |
| Type≠ | Sample size determination for survival outcomes | Sample size determination |
| Oprindelig kilde≠ | Schoenfeld, D. A. (1981). The asymptotic properties of nonparametric tests for comparing survival distributions. Biometrika, 68(1), 316–319. DOI ↗ | Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. DOI ↗ |
| Aliasser | log-rank power analysis, cox regression power analysis, survival power analysis, Sağkalım Analizi Güç Analizi | proportion power analysis, two-proportion z-test power, z-test for proportions power, Oran Testi Güç Analizi |
| Relaterede≠ | 6 | 3 |
| Resumé≠ | 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. | Power analysis for proportion tests is a prospective sample-size planning method used to determine how many participants are needed to detect a meaningful difference between two (or one) proportions with a specified probability. Formalised by Jacob Cohen in his 1988 landmark text, it applies the arcsine transformation to convert proportions into the effect-size index h, enabling direct calculation of the required sample size. |
| ScholarGateDatasæt ↗ |
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