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Gamma-Regression (GLM)×Logistische Regression×
FachgebietStatistikForschungsstatistik
FamilieRegression modelProcess / pipeline
Entstehungsjahr19891958
UrheberMcCullagh & Nelder (GLM framework)David Roxbee Cox
TypGeneralized linear modelMethod
Wegweisende QuelleMcCullagh, P. & Nelder, J. A. (1989). Generalized Linear Models (2nd ed.). Chapman and Hall. DOI ↗Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗
Aliasnamengamma GLM, gamma generalized linear model, Gamma Regresyonu (GLM)logit model, binomial logistic regression, LR
Verwandt43
ZusammenfassungGamma regression is a generalized linear model that uses the gamma distribution to model a positive, right-skewed continuous outcome. Developed within the GLM framework of McCullagh and Nelder (1989), it is an alternative to ordinary linear regression for variables such as health-care costs, durations, and income.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: Gamma Regression · Logistic Regression. Abgerufen am 2026-06-18 von https://scholargate.app/de/compare