Previous research has compared methods of estimation for fitting multilevel models to binary data, but there are reasons to believe that the results will not always generalize to the ordinal case. This article thus evaluates (a) whether and when fitting multilevel linear models to ordinal outcome data is justified and (b) which estimator to employ when instead fitting multilevel cumulative logi...

Longitudinal studies of a binary outcome are common in the health, social, and behavioral sciences. In general, a feature of random effects logistic regression models for longitudinal binary data is that the marginal functional form, when integrated over the distribution of the random effects, is no longer of logistic form. Recently, Wang and Louis (2003) proposed a random intercept model in th...

This paper focuses on the relevance of alternate discrete outcome frameworks for modeling driver injury severity. The study empirically compares the ordered response and unordered response models in the context of driver injury severity in traffic crashes. The alternative modeling approaches considered for the comparison exercise include: for the ordered response framework-ordered logit (OL), g...

One of the most important empirical findings in microeconometrics is pervasiveness heterogeneity economic behavior (cf. Heckman, 2001 ). This paper shows that cumulative distribution functions and quantiles nonparametric unobserved have an infinite efficiency bound many structural models interest. The presents general precise conditions to prove such results. usefulness theory demonstrated with...

Objectives: This exploratory study sought to investigate the impact of cognitive functioning on the consistency of individual responses to a DCE study conducted exclusively with older people. Methods: A DCE to investigate preferences for multidisciplinary rehabilitation was administered to a consenting sample of older patients (aged 65 years and over) following surgery to repair a fractured hip...

Discrete choice models, like the multinomial logit (MNL), have long been recognized for their ability to capture a wide array of transport-related choice phenomena. However, a number of choices are continuous response variables (e.g., location choice, departure time choice, activity duration, and vehicle usage). In this paper, the continuous cross-nested logit (CCNL) model is introduced. The CC...

certain activities of highway construction are particularly sensitive to such weather conditions as soil moisture, precipitation, and daily temperature. Regression analysis is used to obtain three alternative probability models designed to translate observed weather conditions into probabilities for carrying out construction activities. The models were developed using generalized least squares,...

In this study, two-state Markov switching multinomial logit models are proposed for statistical modeling of accident-injury severities. These models assume Markov switching over time between two unobserved states of roadway safety as a means of accounting for potential unobserved heterogeneity. The states are distinct in the sense that in different states accident-severity outcomes are generate...

A computationally attractive model for the analysis of conjoint choice experiments is the mixed multinomial logit model, a multinomial logit model in which it is assumed that the coefficients follow a (normal) distribution across subjects. This model offers the advantage over the standard multinomial logit model of accommodating heterogeneity in the coefficients of the choice model across subje...

Research background: Based on the history of financial crises, real estate market behavior could be thought as a key benchmark trust shifts in sector economy. Plunging asset prices accompanied by "bubbles" explosion viewed harbinger ? even cause public crash sector.
 Purpose article: This study intends to assess extent which determinants, along with consumers' feelings, are able predict cr...