Linganisha mbinu

	Uchambuzi wa uhusiano kati ya kipimo na mwitikio ulioboreshwa kwa hatari	Mfumo wa Cox Proportional Hazards
Nyanja	Epidemiolojia	Epidemiolojia
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	1980s-1990s (formalized in modern epidemiology)	1972
Mwanzilishi	Sander Greenland; Kenneth Rothman (foundational epidemiological methods)	Sir David Roxbee Cox
Aina	Epidemiological modeling technique	Semi-parametric regression model
Chanzo asilia	Greenland, S. (1995). Dose-response and trend analysis in epidemiology: alternatives to categorical analysis. Epidemiology, 6(4), 356-365.	Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202.
Majina mbadala	confounder-adjusted dose-response, covariate-adjusted dose-response modeling, risk-stratified dose-response analysis, adjusted exposure-response analysis	Cox regression, Cox PH model, proportional hazards model, CPH
Zinazohusiana	4	5
Muhtasari	Risk-adjusted dose-response analysis quantifies the relationship between increasing levels of an exposure (dose) and the probability or magnitude of an outcome (response), while simultaneously controlling for baseline risk factors that could confound or modify this relationship. The method is widely applied in clinical epidemiology, pharmacoepidemiology, and environmental health research to isolate the causal contribution of exposure intensity from background risk heterogeneity among participants.	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.