— Caussinus’s loglinear model of quasi symmetry has interesting connections with models for within-subject effects with repeated categorical measurement. For binary responses, Tjur (1982) showed that estimates of main effect parameters in the quasi-symmetry model are also conditional maximum likelihood estimates of item parameters for a fixed effects treatment of subject terms in the Rasch item...

This paper explains how to calculate adjusted risk ratios and risk differences when reporting results from logit, probit, and related nonlinear models. Building on Stata’s margins command, we create a new post-estimation command adjrr that calculates adjusted risk ratios (ARR) and adjusted risk differences (ARD) after running logit or probit models with either binary, multinomial, or ordered ou...

environment, environmental protection and sustainability policies play a key role in social development and in the economic competitiveness of industrialized countries. most european citizens are aware of the importance of environmental issues, both as a priority for the socio-economic system as a whole, and as a relevant factor in influencing quality of life. at the same time individual enviro...

In this paper estimators for distribution free heteroskedastic binary response models are proposed. The estimation procedures are based on relationships between distribution free models with a conditional median restriction and parametric models (such as Probit/Logit) exhibiting (multiplicative) heteroskedasticity. The first proposed estimator is based on the observational equivalence between t...

This paper presents an extension of fixed effects binary choice models for panel data, to the case of heterogeneous linear trends. Two estimators are proposed: a Logit estimator based on double conditioning and a semiparametric, smoothed maximum score estimator based on double differences. We investigate small-sample properties of these estimators with a Monte Carlo simulation experiment, and c...

This paper discusses the representability of discrete logit-type models including multinomial logit and nested logit model from a mathematical approach. It is shown that the logit-type models can be reconstructed from mathematical approximation theory with sigmoidal functions widely used in Neural Network modeling without the basic assumptions such as IIA and iid, and the distribution (or densi...

In this study, the manner of private taxis drivers has been investigated for choosing passenger and destination from a fixed point. Therefore, two models called Multinomial and Nested Logit Models have been utilized. The information gained by scrolling in 2016 is the input data, which are in the format of revealed preference, acquired by the verbal interview in Vanak Square in Tehran (Iran). Ba...

The generalized nested logit model is a new member of the generalized extreme value family of models. The GNL provides a higher degree of flexibility in the estimation of substitution or cross-elasticity between pairs of alternatives than previously developed generalized extreme value models. The generalized nested logit model includes the paired combinatorial logit and cross-nested logit model...