Comparer des méthodes

	Modèle Logit Conditionnel (McFadden)	Modèle Logit Mixte
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1974	2000
Auteur d'origine	Daniel McFadden	Daniel McFadden & Kenneth Train
Type	Discrete choice model for alternative-specific covariates	Random-parameters discrete choice model
Source fondatrice	McFadden, D. (1974). Conditional logit analysis of qualitative choice behavior. In P. Zarembka (Ed.), Frontiers in Econometrics (pp. 105–142). Academic Press. ISBN: 978-0-12-776150-3	Train, K. E. (2009). Discrete Choice Methods with Simulation (2nd ed.). Cambridge University Press. ISBN: 978-0-521-74738-7
Alias	McFadden's Choice Model, Discrete Choice Logit, Alternative-Specific Logit, Koşullu Logit Modeli	Random Parameters Logit, Mixed Multinomial Logit, Error Components Logit, Karma Logit Modeli
Apparentées	3	3
Résumé	The Conditional Logit Model, introduced by Daniel McFadden in 1974, is a discrete-choice econometric model designed to explain an individual's selection among a finite set of mutually exclusive alternatives. Unlike multinomial logit, it uses covariates that vary across alternatives — such as price, travel time, or product attributes — making it ideally suited for revealed-preference studies in transportation, marketing, and labor economics.	The Mixed Logit model, introduced formally by McFadden and Train (2000) and elaborated in Train (2009), is a flexible discrete choice framework that allows preference parameters to vary randomly across decision-makers. By integrating standard logit probabilities over a mixing distribution of coefficients, it overcomes the restrictive independence of irrelevant alternatives (IIA) property and accommodates unobserved taste heterogeneity, panel data correlation, and complex substitution patterns across alternatives.