Linganisha mbinu

	Usalama wa Cox wa Matarajio	Mfumo wa Cox Proportional Hazards
Nyanja	Epidemiolojia	Epidemiolojia
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	1972 (Cox model); widespread prospective application from late 1970s	1972
Mwanzilishi	David R. Cox (model); applied prospectively in large cohort studies from 1970s onward	Sir David Roxbee Cox
Aina	Semi-parametric survival regression applied to prospectively collected time-to-event data	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	prospective Cox regression, Cox PH prospective study, prospective survival regression, prospective hazard modeling	Cox regression, Cox PH model, proportional hazards model, CPH
Zinazohusiana	4	5
Muhtasari	Prospective Cox proportional hazards regression combines a forward-looking cohort design — in which participants are enrolled before outcomes occur and followed over time — with Cox's semi-parametric survival model. The method estimates how baseline covariates measured at enrollment influence the rate at which participants experience a time-to-event outcome, while preserving the temporal direction required for causal inference. It is one of the most widely used analytical frameworks in clinical epidemiology and chronic disease 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.