Understanding the underlying relationship between crash injury severity and factors such as driver’s characteristics, vehicle type, and roadway conditions is very important for improving traffic safety. Most previous studies on this topic used traditional statistical models such as ordered probit OP , multinomial logit, and nested logit models. This research introduces the Bayesian inference an...

Most genomic-enabled prediction models developed so far assume that the response variable is continuous and normally distributed. The exception is the probit model, developed for ordered categorical phenotypes. In statistical applications, because of the easy implementation of the Bayesian probit ordinal regression (BPOR) model, Bayesian logistic ordinal regression (BLOR) is implemented rarely ...

AIM The aim of this study was to determine whether there is relation between body mass index and symptoms of gastro-esophageal reflux disease in our community using Logit, Probit and Complementary log-log models. BACKGROUND The most frequent statistical tool to address the relationship among a dichotomous response and other covariates is logistic regression. However logistic regression is fam...

Social scientists, particularly political scientists, frequently use ordinal survey items as dependent variables in models of political attitudes. Commonly, normal-theory modeling strategies like ordinary least squares regression are applied to these items. Additionally, workers also make frequent use of the proportional odds (ordinal logit) model or cumulative probit model when working with su...

Pedestrians are the most vulnerable road users. For evaluating and modifying pedestrian safety in unsignalized crosswalks,the first important issue is to identify and explore factors affecting the interaction behavior of pedestrians andvehicles in conflict areas. By analyzing those factors and determining how they affect road user's behavior, we canrepresent the plans and proc...

Estimation of disaggregate mode choice models to estimate the ridership share on a proposed new (or improved) intercity travel service and to identify the modes from which existing intercity travelers will be diverted to the new or upgraded service constitutes a critical part of evaluating alternative travel service proposals to alleviate intercity travel congestion. This paper develops a new h...

Binary choice models occur frequently in economic modeling. A measure of the predictive performance of binary choice models that is often reported is the hit rate of a model. This paper develops a test for the outperformance of a predictor for binary outcomes over a naive prediction method, which predicts the outcome that is most often observed. This is done for a general class of prediction mo...

Fixed effects estimators of nonlinear panel models can be severely biased due to the incidental parameters problem. In this paper I find that the most important component of this incidental parameters bias for probit fixed effects estimators of index coefficients is proportional to the true value of these coefficients, using a large-T expansion of the bias. This result allows me to derive a low...

This paper proposes an original and unified toolbox to evaluate financial crisis Early Warning Systems (EWS). It presents four main advantages. First, it is a model free method which can be used to asses the forecasts issued from different EWS (probit, logit, markov switching models, or combinations of models). Second, this toolbox can be applied to any type of crisis EWS (currency, banking, so...