Linganisha mbinu

	Cox ya Hatari Husababishwa na Hatari	Mfumo wa Cox Proportional Hazards
Nyanja	Epidemiolojia	Epidemiolojia
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	1972 (Cox model); risk adjustment widespread from 1980s	1972
Mwanzilishi	D. R. Cox (base model); risk-adjustment as routine practice formalised through clinical epidemiology literature from the 1980s onward	Sir David Roxbee Cox
Aina	Multivariable survival regression	Semi-parametric regression model
Chanzo asilia	Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202.	Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202.
Majina mbadala	adjusted Cox regression, multivariable Cox model, covariate-adjusted survival analysis, risk-adjusted survival model	Cox regression, Cox PH model, proportional hazards model, CPH
Zinazohusiana	5	5
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 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.