scholarly journals Driver injury severity: an application of ordered probit models

2002 ◽  
Vol 34 (3) ◽  
pp. 313-321 ◽  
Author(s):  
Kara Maria Kockelman ◽  
Young-Jun Kweon
2013 ◽  
Vol 57 ◽  
pp. 55-66 ◽  
Author(s):  
Ximiao Jiang ◽  
Baoshan Huang ◽  
Russell L. Zaretzki ◽  
Stephen Richards ◽  
Xuedong Yan ◽  
...  

2020 ◽  
pp. 1-6
Author(s):  
Zhao Zhang ◽  
Runan Yang ◽  
Yun Yuan ◽  
Glenn Blackwelder ◽  
Xianfeng (Terry) Yang

2002 ◽  
Vol 31 (2) ◽  
pp. 157-170 ◽  
Author(s):  
R. Wes Harrison ◽  
Timothy Stringer ◽  
Witoon Prinyawiwatkul

Conjoint analysis is used to evaluate consumer preferences for three consumer-ready products derived from crawfish. Utility functions are estimated using two-limit tobit and ordered probit models. The results show women prefer a baked nugget or popper type product, whereas 35- to 44-year-old men prefer a microwavable nugget or patty type product. The results also show little difference between part-worth estimates or predicted rankings for the tobit and ordered probit models, implying the results are not sensitive to assumptions regarding the ordinal and cardinal nature of respondent preferences.


2002 ◽  
Vol 33 (4) ◽  
pp. 445-462 ◽  
Author(s):  
Mohammed A. Quddus ◽  
Robert B. Noland ◽  
Hoong Chor Chin

Author(s):  
Francisco Corona ◽  
Juan de Dios Tena Horrillo ◽  
Michael Peter Wiper

AbstractIdentifying the decisive matches in international football tournaments is of great relevance for a variety of decision makers such as organizers, team coaches and/or media managers. This paper addresses this issue by analyzing the role of the statistical approach used to estimate the outcome of the game on the identification of decisive matches on international tournaments for national football teams. We extend the measure of decisiveness proposed by Geenens (2014) in order to allow us to predict or evaluate the decisive matches before, during and after a particular game on the tournament. Using information from the 2014 FIFA World Cup, our results suggest that Poisson and kernel regressions significantly outperform the forecasts of ordered probit models. Moreover, we find that although the identification of the most decisive matches is independent of the model considered, the identification of other key matches is model dependent. We also apply this methodology to identify the favorite teams and to predict the most decisive matches in 2015 Copa America before the start of the competition. Furthermore, we compare our forecast approach with respect to the original measure during the knockout stage.


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