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Cox-Proportional-Hazards-Modell×Logistische Regression×
FachgebietEpidemiologieForschungsstatistik
FamilieProcess / pipelineProcess / pipeline
Entstehungsjahr19721958
UrheberSir David Roxbee CoxDavid Roxbee Cox
TypSemi-parametric regression modelMethod
Wegweisende QuelleCox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202. DOI ↗Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗
AliasnamenCox regression, Cox PH model, proportional hazards model, CPHlogit model, binomial logistic regression, LR
Verwandt53
ZusammenfassungThe 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.
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ScholarGateMethoden vergleichen: Cox proportional hazards · Logistic Regression. Abgerufen am 2026-06-19 von https://scholargate.app/de/compare