ScholarGate
Assistente

Comparar métodos

Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.

Análise de Potência para Estudos de Sobrevivência×Cox Proportional Hazards×
ÁreaEstatísticaEpidemiologia
FamíliaHypothesis testProcess / pipeline
Ano de origem19811972
Autor originalSir David Roxbee Cox
TipoSample size determination for survival outcomesSemi-parametric regression model
Fonte seminalSchoenfeld, 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 ↗
Outros nomeslog-rank power analysis, cox regression power analysis, survival power analysis, Sağkalım Analizi Güç AnaliziCox regression, Cox PH model, proportional hazards model, CPH
Relacionados65
ResumoPower 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.
ScholarGateConjunto de dados
  1. v1
  2. 2 Fontes
  3. PUBLISHED
  1. v1
  2. 2 Fontes
  3. PUBLISHED

Ir para a pesquisa Baixar slides

ScholarGateComparar métodos: Survival Analysis Power Analysis · Cox proportional hazards. Recuperado em 2026-06-19 de https://scholargate.app/pt/compare