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Bivariat Probitmodell×Multinomial logistisk regresjon×
FagfeltØkonometriØkonometri
FamilieRegression modelRegression model
Opprinnelsesår19701974
OpphavspersonJ. R. Ashford & R. R. SowdenMcFadden
TypeMaximum-likelihood binary outcome modelMultinomial logistic regression
Opprinnelig kildeAshford, J. R., & Sowden, R. R. (1970). Multi-variate probit analysis. Biometrics, 26(3), 535–546. DOI ↗McFadden, D. (1974). Conditional Logit Analysis of Qualitative Choice Behavior. In P. Zarembka (Ed.), Frontiers in Econometrics (pp. 105-142). Academic Press. ISBN: 978-0127761503
AliasBivariate Binary Probit, Joint Probit Model, Two-Equation Probit, İki Değişkenli Probitmultinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyon
Relaterte35
SammendragThe Bivariate Probit Model, introduced by Ashford and Sowden (1970), jointly estimates two binary outcome equations whose error terms are allowed to be correlated. By modeling both outcomes simultaneously under a bivariate normal distribution, it corrects for the dependence between decisions that separate probit regressions would ignore, producing consistent and efficient parameter estimates for researchers studying interrelated binary choices.Multinomial 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.
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ScholarGateSammenlign metoder: Bivariate Probit · Multinomial Logit. Hentet 2026-06-15 fra https://scholargate.app/no/compare