Сравнение методов

	Анализ зависимости «доза-эффект» с поправкой на риск	Регрессионная модель пропорциональных рисков Кокса
Область	Эпидемиология	Эпидемиология
Семейство	Process / pipeline	Process / pipeline
Год появления	1980s-1990s (formalized in modern epidemiology)	1972
Автор метода	Sander Greenland; Kenneth Rothman (foundational epidemiological methods)	Sir David Roxbee Cox
Тип	Epidemiological modeling technique	Semi-parametric regression model
Основополагающий источник	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.
Другие названия	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
Связанные	4	5
Сводка	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.