Applications of Subset Selection Procedures and Bayesian Ranking Methods in Analysis of Traffic Fatality Data
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Date
2016-11
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
WIREs Computational Statistics
Abstract
Nonparametric and parametric subset selection procedures are used in the analysis of state motor vehicle traffic fatality rates (MVTFRs), for the years 1994 through 2012, to identify subsets of states that contain the ‘best’ (lowest MVTFR) and ‘worst’ (highest MVTFR) states with a prescribed probability. A new Bayesian model is developed and applied to the traffic fatality data and the results contrasted to those obtained with the subset selection procedures. All analyses are applied within the context of a two-way block design.
Description
Keywords
Probability of a correct selection, Fatality analysis reporting system, Bayesian inference, WinBugs, Additive model, Tukey one-degree-of-freedom test for additivity
Citation
WIREs Comput Stat 2016, 8:222–237. doi: 10.1002/wics.1385