Σύγκριση μεθόδων

	Μοντέλο Αναλογικών Κινδύνων Cox	Λογιστική Παλινδρόμηση
Πεδίο	Επιδημιολογία	Ερευνητική Στατιστική
Οικογένεια	Process / pipeline	Process / pipeline
Έτος προέλευσης	1972	1958
Δημιουργός	Sir David Roxbee Cox	David Roxbee Cox
Τύπος	Semi-parametric regression model	Method
Θεμελιώδης πηγή	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. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242.
Εναλλακτικές ονομασίες	Cox regression, Cox PH model, proportional hazards model, CPH	logit model, binomial logistic regression, LR
Συναφείς	5	3
Σύνοψη	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.	Logistic regression is a statistical method for modeling the probability of a binary outcome (disease present/absent, success/failure) as a function of continuous and categorical predictors. Developed by David Roxbee Cox (1958), it solves the problem of predicting categorical outcomes by applying a logistic transformation to constrain predictions to the [0,1] probability interval, enabling accurate risk stratification, diagnostic prediction, and causal inference in epidemiology, medicine, and social science.