ScholarGate
Pembantu

Bandingkan kaedah

Semak kaedah pilihan anda secara bersebelahan; baris yang berbeza akan diserlahkan.

Analisis Kuasa untuk Kajian Survival×Regresi Bahaya Berkadaran Cox×
BidangStatistikEpidemiologi
KeluargaHypothesis testProcess / pipeline
Tahun asal19811972
PengasasSir David Roxbee Cox
JenisSample size determination for survival outcomesSemi-parametric regression model
Sumber perintisSchoenfeld, D. A. (1981). The asymptotic properties of nonparametric tests for comparing survival distributions. Biometrika, 68(1), 316–319. DOI ↗Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202. DOI ↗
Aliaslog-rank power analysis, cox regression power analysis, survival power analysis, Sağkalım Analizi Güç AnaliziCox regression, Cox PH model, proportional hazards model, CPH
Berkaitan65
RingkasanPower 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 Cox proportional hazards model is a semi-parametric regression method that estimates the effect of one or more covariates on the hazard — the instantaneous rate of an event such as death, relapse, or failure — while making no assumption about the shape of the baseline hazard function. Introduced by David Cox in 1972, it is the dominant tool for multivariable survival analysis in clinical and epidemiological research.
ScholarGateSet data
  1. v1
  2. 2 Sumber
  3. PUBLISHED
  1. v1
  2. 2 Sumber
  3. PUBLISHED

Pergi ke carian Muat turun slaid

ScholarGateBandingkan kaedah: Survival Analysis Power Analysis · Cox proportional hazards. Dicapai 2026-06-19 daripada https://scholargate.app/ms/compare