Módszerek összehasonlítása

	Fine-Gray kompenzáló kockázati modell	Log-rank teszt túlélési görbék összehasonlítására
Tudományterület	Statisztika	Túléléselemzés
Módszercsalád	Hypothesis test	Survival analysis
Keletkezés éve	1999	1966
Megalkotó	Jason P. Fine & Robert J. Gray	Mantel, N.
Típus	Subdistribution hazard regression	Non-parametric hypothesis test
Alapmű	Fine, J.P. & Gray, R.J. (1999). A Proportional Hazards Model for the Subdistribution of a Competing Risk. Journal of the American Statistical Association, 94(446), 496–509.	Mantel, N. (1966). Evaluation of Survival Data and Two New Rank Order Statistics Arising in Its Consideration. Cancer Chemotherapy Reports, 50(3), 163–170.
Alternatív nevek	competing risks regression, subdistribution hazard model, Fine-Gray model, Fine-Gray Competing Risks Modeli	Mantel log-rank test, Mantel-Cox test, log-rank sağkalım testi, Log-Rank Testi
Kapcsolódó	5	2
Összefoglaló	The Fine-Gray model is a semiparametric regression method for survival data in which two or more mutually exclusive event types compete to occur first. Proposed by Fine and Gray in 1999, it models the subdistribution hazard of each event type directly, allowing covariates to be linked to the cumulative incidence function (CIF) — the quantity that actually answers 'what is the probability of experiencing event type k by time t?'. It corrects the well-known shortcoming of standard Cox regression, which ignores competing events and thereby overestimates cause-specific probabilities.	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.