Using a flexible multivariate latent class approach to model correlated outcomes: A joint analysis of pedestrian and cyclist injuries

Heydari, Shahram; Fu, Liping; Miranda-Moreno, Luis F.; Jopseph, Lawrence

doi:10.1016/j.amar.2016.12.002

Cited by 64 publications

(22 citation statements)

References 86 publications

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“…Several studies recognizing the importance of unobserved heterogeneity have developed multivariate approaches that account for the potential dependency across count variables. The various model structures developed from multivariate models include multivariate Poisson regression model (Ye et al, 2009), multivariate Poisson lognormal model (Serhiyenko et al, 2016), multinomialgeneralized Poisson model (Chiou and Fu, 2013), multivariate Poisson gamma mixture count model (Mothafer et al, 2016), multivariate Poisson lognormal spatial and temporal model (Aguero-Valverde et al, 2016;Cheng et al, 2017), Integrated Nested Laplace Approximation Multivariate Poisson Lognormal model (Wang et al, 2017), Bayesian latent class flexible mixture multivariate model (Heydari et al, 2017) and multivariate random-parameters zeroinflated negative binomial model (Anastasopoulos, 2016).…”

Section: Earlier Researchmentioning

confidence: 99%

A joint econometric approach for modeling crash counts by collision type

Bhowmik

Yasmin

Eluru

2018

Analytic Methods in Accident Research

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In recent years, there is growing recognition that common unobserved factors that influence crash frequency by one attribute level are also likely to influence crash frequency by other attribute levels. The most common approach employed to address the potential unobserved heterogeneity in safety literature is the development of multivariate crash frequency models. The current study proposes an alternative joint econometric framework to accommodate for the presence of unobserved heterogeneityreferred to as joint negative binomial-multinomial logit fractional split (NB-MNLFS) model. Furthermore, the study undertakes a first of its kind comparison exercise between the most commonly used multivariate model (multivariate random parameter negative binomial model) and the proposed joint approach by generating an equivalent log-likelihood measure. The empirical analysis is based on the zonal level crash count data for different collision types from the state of Florida for the year 2015. The model results highlight the presence of common unobserved effects affecting the two components of the joint model as well as the presence of parameter heterogeneity. The equivalent log-likelihood and goodness of fit measures clearly highlight the superiority of the proposed joint model over the commonly used multivariate approach. ` iv ACKNOWLEDGMENT I would like to convey my heartiest gratitude to my honorable supervisor Dr. Naveen Eluru for his excellent supervision and being a constant support in this thesis. I would also like to gratefully acknowledge Signal Four Analytics (S4A) and Florida Department of Transportation (FDOT) for providing access to Florida crash and geospatial data. I would like to convey my heartiest gratitude to Dr. Shamsunnahar Yasmin who helped me a lot throughout the journey in University of Central Florida and guide me through the thesis.

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Section: Earlier Researchmentioning

confidence: 99%

A joint econometric approach for modeling crash counts by collision type

Bhowmik

Yasmin

Eluru

2018

Analytic Methods in Accident Research

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“…Originally developed in biostatistics [40], this model was brought into the social sciences in the 1970s, and recently, it has been widely applied in transportation studies. In greater detail, several applications can be found in vehicle ownership analysis [41], road safety and injury models [42,43], determinants of bicycle choice [44], cyclists' travel behavior [45], and car sharing usage [46].…”

Section: Statistical Modelmentioning

confidence: 99%

Flexible Mobile Hub for E-Bike Sharing and Cruise Tourism: A Case Study

Bardi¹,

Mantecchini

Grasso³

et al. 2019

Sustainability

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Bike sharing is no longer a novelty in transportation and has now become a mobility solution in its own right. This study investigated the potential scope of application of e-bike sharing solutions for a niche sector such as cruise tourism, the importance of which is growing, with the aim of improving sustainability and reducing pollution levels in cruise ports. A revealed preference survey was administered to cruise tourists, who chose a pilot e-bike service once they had disembarked from the ship to visit the nearby city center, to investigate the main variables affecting satisfaction with the service under investigation. An ordered probit model was specified and calibrated to identify the relationship among the variables influencing e-bike sharing usage by cruise tourists and their satisfaction. Subsequently, the marginal effect of each significant factor was evaluated to quantify its actual impact on the related e-bike sharing satisfaction level. The results obtained are consistent with the literature, but interesting interpretations are provided in terms of the relative importance of significant variables.

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“…Broadly speaking, the exposure measure is rather conceptual, and direct measurement may not be feasible in many situations. In practice, although the use of exposure measures is constrained by the availability and quality of data (Naci et al, 2009), various proxy measures have been developed and used in different crash frequency analyses, including population and fuel consumption (Amoh-Gyimah et al, 2017;Fridstrøm et al, 1995), traffic volume (Chiou and Fu, 2015;Heydari et al, 2017;Qin et al, 2004Qin et al, , 2006Wong et al, 2007), travel time (Chipman et al, 1993;Imprialou et al, 2016), vehicle-miles traveled (Li et al, 2003;Pei et al, 2016), potential conflict counts (Bie et al, 2005;Wong et al, 2006), and quasi-induced exposure (Huang and Chin, 2009;Jiang et al, 2014;Stamatiadis and Deacon, 1997).…”

Section: Introductionmentioning

confidence: 99%

“…The products of the different combinations of conflicting disaggregated flows were considered to indicate the conflicting volumes. Similar concepts have been included in a more advanced model-the latent class model with Bayesian inference-to study the unobserved heterogeneity in pedestrian and cyclist crashes (Heydari et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Gas dynamic analogous exposure approach to interaction intensity in multiple-vehicle crash analysis: Case study of crashes involving taxis

Meng

Wong

et al. 2017

Analytic Methods in Accident Research

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Exposure is a frequency measure of being in situations in which crashes could occur. In modeling multiple-vehicle crash frequency, traditional exposure measures, such as vehicle kilometrage and travel time, may not be sufficiently representative because they may include situations in which vehicles rarely meet each other and multiple-vehicle crashes can never happen. The meeting frequency of vehicles should be a better exposure measure in such cases. This study aims to propose a novel Gas Dynamic Analogous Exposure (GDAE) to model multiple-vehicle crash frequency. We analogize the meeting frequency of vehicles with the meeting frequency of gas molecules because both systems consider the numbers of the meetings of discrete entities. A meeting frequency function of vehicles is derived based on the central idea of the classical collision theory in physical chemistry with consideration of constrained vehicular movement by the road alignments. The GDAE is then formulated on

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Using a flexible multivariate latent class approach to model correlated outcomes: A joint analysis of pedestrian and cyclist injuries

Cited by 64 publications

References 86 publications

A joint econometric approach for modeling crash counts by collision type

A joint econometric approach for modeling crash counts by collision type

Flexible Mobile Hub for E-Bike Sharing and Cruise Tourism: A Case Study

Gas dynamic analogous exposure approach to interaction intensity in multiple-vehicle crash analysis: Case study of crashes involving taxis

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