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A Representative Consumer Theory of the Logit Model
International Economic Review, 1988Discrete choice models (to be more precise: logit models) are usually employed to describe consumers' behavior when they are faced with a variety of mutually exclusive choices. Within this framework, total consumption is treated as given. In the present paper the authors first derive the demand functions and the direct utility function for a ...
Anderson, Simon Peter +2 more
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The Stata Journal: Promoting communications on statistics and Stata, 2022
The parameters of logit models are typically difficult to interpret, and the applied literature is replete with interpretive and computational mistakes. In this article, I review a menu of options to interpret the results of logistic regressions correctly and effectively using Stata.
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The parameters of logit models are typically difficult to interpret, and the applied literature is replete with interpretive and computational mistakes. In this article, I review a menu of options to interpret the results of logistic regressions correctly and effectively using Stata.
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Testing logit models in practice
Empirical Economics, 1991The aim of the paper is to provide the practioner with easily implementable procedures, both numerical and graphical, to test the specification of the dichotomous, linear-in-coefficents logit model. We discuss the performance of these asymptotic methods in small samples on the basis of Monte-Carlo simulations and apply them to a cross-section study of ...
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1990
In chapters 4, 5 and 6 the categorical variables appeared in the model in a symmetrical way. In many situations, for example in examples 6.1 and 6.2 in chapter 6, one of the variable is of special interest. For the survival data in example 6.1, survival is the variable of special interest, and the problem is to study if the other three variables have ...
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In chapters 4, 5 and 6 the categorical variables appeared in the model in a symmetrical way. In many situations, for example in examples 6.1 and 6.2 in chapter 6, one of the variable is of special interest. For the survival data in example 6.1, survival is the variable of special interest, and the problem is to study if the other three variables have ...
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Transportation Research Part B: Methodological, 1991
The logit model is the simplest and best-known probabilistic choice model. Nevertheless according to the deficient flexibility there are problems of making use of the multinomial logit model. In this paper a generalized logit model, which is essentially more flexible than the traditional multinomial logit model, is presented.
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The logit model is the simplest and best-known probabilistic choice model. Nevertheless according to the deficient flexibility there are problems of making use of the multinomial logit model. In this paper a generalized logit model, which is essentially more flexible than the traditional multinomial logit model, is presented.
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Transportation Research Part A: Policy and Practice, 2013
A novel logit-type discrete choice model is presented whose distinctive characteristic is that it "polarizes" or forces the prediction of choice probabilities towards values of 0 or 1. In real-world empirical tests this property enabled the new formulation, which we call the polarized logit model (PLM), to outperform the predictive capacity of other ...
De Grange, Louis +3 more
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A novel logit-type discrete choice model is presented whose distinctive characteristic is that it "polarizes" or forces the prediction of choice probabilities towards values of 0 or 1. In real-world empirical tests this property enabled the new formulation, which we call the polarized logit model (PLM), to outperform the predictive capacity of other ...
De Grange, Louis +3 more
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2014
The ordered logit model is a regression model for an ordinal response variable. The model is based on the cumulative probabilities of the response variable: in particular, the logit of each cumulative probability is assumed to be a linear function of the covariates with regression coefficients constant across response categories.
Grilli, Leonardo, Rampichini, Carla
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The ordered logit model is a regression model for an ordinal response variable. The model is based on the cumulative probabilities of the response variable: in particular, the logit of each cumulative probability is assumed to be a linear function of the covariates with regression coefficients constant across response categories.
Grilli, Leonardo, Rampichini, Carla
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2014
Das erste Problem, das bei der Untersuchung des Zusammenhangs zwischen einer dichotomen abhangigen Variablen und einer oder mehreren intervallskalierten und kontinuierlichen unabhangigen Variablen auftritt, besteht in der Suche nach einer geeigneten Gleichung fur diesen Zusammenhang bzw. fur eine geeignete Form der Gleichung.
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Das erste Problem, das bei der Untersuchung des Zusammenhangs zwischen einer dichotomen abhangigen Variablen und einer oder mehreren intervallskalierten und kontinuierlichen unabhangigen Variablen auftritt, besteht in der Suche nach einer geeigneten Gleichung fur diesen Zusammenhang bzw. fur eine geeignete Form der Gleichung.
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1992
Statistical models in which the endogenous random variables take only discrete values are known as discrete, categorical, qualitative — choice, or quanta! response models.1 This class of models was originally developed by psychologists and later adapted and extended by economists for describing consumers choices. These models have numerous applications
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Statistical models in which the endogenous random variables take only discrete values are known as discrete, categorical, qualitative — choice, or quanta! response models.1 This class of models was originally developed by psychologists and later adapted and extended by economists for describing consumers choices. These models have numerous applications
openaire +1 more source