Linganisha mbinu

	Cox ya Hatari Husababishwa na Hatari	Kipimo cha Log-Rank cha Kulinganisha Milia ya Uhai
Nyanja	Epidemiolojia	Uchanganuzi wa Uhai
Familia	Process / pipeline	Survival analysis
Mwaka wa asili	1972 (Cox model); risk adjustment widespread from 1980s	1966
Mwanzilishi	D. R. Cox (base model); risk-adjustment as routine practice formalised through clinical epidemiology literature from the 1980s onward	Mantel, N.
Aina	Multivariable survival regression	Non-parametric hypothesis test
Chanzo asilia	Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202.	Mantel, N. (1966). Evaluation of Survival Data and Two New Rank Order Statistics Arising in Its Consideration. Cancer Chemotherapy Reports, 50(3), 163–170.
Majina mbadala	adjusted Cox regression, multivariable Cox model, covariate-adjusted survival analysis, risk-adjusted survival model	Mantel log-rank test, Mantel-Cox test, log-rank sağkalım testi, Log-Rank Testi
Zinazohusiana	5	2
Muhtasari	Risk-adjusted Cox proportional hazards regression extends the classical Cox (1972) survival model by simultaneously entering known confounders — age, sex, comorbidities, disease severity — into the model alongside the exposure of primary interest. This adjustment isolates the independent effect of the exposure on the hazard of an event, producing hazard ratios (HRs) that are not distorted by baseline differences between comparison groups. It is the most widely used method for multivariable survival analysis in clinical and epidemiological research.	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.