Sammenlign metoder

	Styrkeanalyse for overlevelsesstudier	Styrkeanalyse for proporsjonstester
Fagfelt	Statistikk	Statistikk
Familie	Hypothesis test	Hypothesis test
Opprinnelsesår	1981	1988
Opphavsperson	—	Jacob Cohen
Type	Sample size determination for survival outcomes	Sample size determination
Opprinnelig kilde	Schoenfeld, D. A. (1981). The asymptotic properties of nonparametric tests for comparing survival distributions. Biometrika, 68(1), 316–319.	Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates.
Alias	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
Relaterte	6	3
Sammendrag	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.