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Multinominale logistische regressie×Logistische Regressie×
VakgebiedEconometrieOnderzoeksstatistiek
FamilieRegression modelProcess / pipeline
Jaar van ontstaan19741958
GrondleggerMcFaddenDavid Roxbee Cox
TypeMultinomial logistic regressionMethod
Oorspronkelijke bronMcFadden, D. (1974). Conditional Logit Analysis of Qualitative Choice Behavior. In P. Zarembka (Ed.), Frontiers in Econometrics (pp. 105-142). Academic Press. ISBN: 978-0127761503Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗
Aliassenmultinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyonlogit model, binomial logistic regression, LR
Verwant53
SamenvattingMultinomial logistic regression is a maximum-likelihood method for a nominal (unordered) dependent variable with more than two categories. Building on McFadden's 1974 treatment of qualitative choice, it gives each category its own set of coefficients relative to a reference category.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 vergelijken: Multinomial Logit · Logistic Regression. Geraadpleegd op 2026-06-17 via https://scholargate.app/nl/compare