ScholarGate
Assistent

Compara mètodes

Revisa els mètodes seleccionats l'un al costat de l'altre; les files que difereixen es ressalten.

Anàlisi de supervivència aparellada×Test Log-Rank per a Comparar Corbes de Supervivència×
CampEpidemiologiaSupervivència
FamíliaProcess / pipelineSurvival analysis
Any d'origen1983 (propensity-score matching); applied to survival outcomes throughout 1990s–2000s1966
Autor originalBuilding on Kaplan & Meier (1958) and Cox (1972); matching framework formalised in observational study design literature (Rosenbaum & Rubin, 1983)Mantel, N.
TipusObservational study analytic methodNon-parametric hypothesis test
Font seminalAustin, P. C. (2014). Graphical assessments of the balance of propensity score matched samples: A SAS macro. Journal of Statistical Software, 58(7), 1-29. Also see Austin, P. C. (2017). A tutorial on multilevel survival analysis: Methods, models and applications. International Statistical Review, 85(2), 185-203. link ↗Mantel, N. (1966). Evaluation of Survival Data and Two New Rank Order Statistics Arising in Its Consideration. Cancer Chemotherapy Reports, 50(3), 163–170. link ↗
Àliesmatched time-to-event analysis, propensity-matched survival analysis, matched Kaplan-Meier analysis, paired survival analysisMantel log-rank test, Mantel-Cox test, log-rank sağkalım testi, Log-Rank Testi
Relacionats42
ResumMatched survival analysis combines a matching design — typically propensity score matching or exact matching on key covariates — with time-to-event methods such as Kaplan-Meier estimation and the Cox proportional hazards model. By pairing treated and control subjects who are similar on observed confounders before estimating survival curves or hazard ratios, the approach reduces confounding bias in non-randomised studies and produces more credible comparisons of event-free survival between exposure groups.The log-rank test, developed by Nathan Mantel in 1966, is a non-parametric hypothesis test that compares the overall survival experience of two or more groups throughout the entire follow-up period. It is the standard companion to Kaplan-Meier curves and determines whether observed differences between curves are statistically meaningful.
ScholarGateConjunt de dades
  1. v1
  2. 2 Fonts
  3. PUBLISHED
  1. v1
  2. 2 Fonts
  3. PUBLISHED

Ves a la cerca Baixa les diapositives

ScholarGateCompara mètodes: Matched Survival Analysis · Log-Rank Test. Recuperat el 2026-06-18 de https://scholargate.app/ca/compare