Bandingkan metode

	Regresi Bahaya Proporsional yang Disesuaikan Risiko	Uji Log-Rank untuk Membandingkan Kurva Kelangsungan Hidup
Bidang	Epidemiologi	Analisis Survival
Keluarga	Process / pipeline	Survival analysis
Tahun asal	1972 (Cox model); risk adjustment widespread from 1980s	1966
Pencetus	D. R. Cox (base model); risk-adjustment as routine practice formalised through clinical epidemiology literature from the 1980s onward	Mantel, N.
Tipe	Multivariable survival regression	Non-parametric hypothesis test
Sumber perintis	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.
Alias	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
Terkait	5	2
Ringkasan	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.