Estimating Safety by the Empirical Bayes Method: A Tutorial

2002 ◽  
Vol 1784 (1) ◽  
pp. 126-131 ◽  
Author(s):  
Ezra Hauer ◽  
Douglas W. Harwood ◽  
Forrest M. Council ◽  
Michael S. Griffith
Keyword(s):  
Professional Practice ◽  
Empirical Bayes ◽  
Highway Safety ◽  
Design Model ◽  
Bayes Method ◽  
Safety Improvement ◽  
Safety Design ◽  
Empirical Bayes Method ◽  
History Of ◽  
Safety Estimation

The empirical Bayes (EB) method addresses two problems of safety estimation: it increases the precision of estimates beyond what is possible when one is limited to the use of a 2- to 3-year accident history, and it corrects for the regression-to-mean bias. The increase in precision is important when the usual estimate is too imprecise to be useful. The elimination of the regression-to-mean bias is important whenever the accident history of the entity is in some way connected with the reason why its safety is estimated. The theory of the EB method is well developed. It is now used in the Interactive Highway Safety Design Model and will be used in the Comprehensive Highway Safety Improvement Model. The time has come for the EB method to be the standard and staple of professional practice. The study’s goal is to facilitate the transition from theory into practice.

scholarly journals Identifying Expressway Accident Black Spots Based on the Secondary Division of Road Units

2021 ◽  
Vol 33 (5) ◽  
pp. 731-743
Author(s):  
Guohua Liang ◽  
Xujiao Sun ◽  
Yidan Zhang ◽  
Mingli Chen ◽  
Wanting Zhang
Keyword(s):  
Empirical Bayes ◽  
Traffic Accidents ◽  
Prediction Models ◽  
Control Method ◽  
Bayes Method ◽  
Accident Prediction ◽  
Related Data ◽  
Black Spots ◽  
Empirical Bayes Method ◽  
Safety Estimation

For the purpose of reducing the harm of expressway traffic accidents and improving the accuracy of traffic accident black spots identification, this paper proposes a method for black spots identification of expressway accidents based on road unit secondary division and empirical Bayes method. Based on the modelling ideas of expressway accident prediction models in HSM (Highway Safety Manual), an expressway accident prediction model is established as a prior distribution and combined with empirical Bayes method safety estimation to obtain a Bayes posterior estimate. The posterior estimated value is substituted into the quality control method to obtain the black spots identification threshold. Finally, combining the Xi'an-Baoji expressway related data and using the method proposed in this paper, a case study of Xibao Expressway is carried out, and sections 9, 19, and 25 of Xibao Expressway are identified as black spots. The results show that the method of secondary segmentation based on dynamic clustering can objectively describe the concentration and dispersion of accident spots on the expressway, and the proposed black point recognition method based on empirical Bayes method can accurately identify accident black spots. The research results of this paper can provide a basis for decision-making of expressway management departments, take targeted safety improvement measures.

scholarly journals Safety Effects of Freeway Hard Shoulder Running

2019 ◽  
Vol 9 (17) ◽  
pp. 3614
Author(s):  
Jaisung Choi ◽  
Richard Tay ◽  
Sangyoup Kim ◽  
Seungwon Jeong ◽  
Jeongmin Kim ◽  
...  
Keyword(s):  
South Korea ◽  
Empirical Bayes ◽  
Positive Relationship ◽  
Crash Severity ◽  
Bayes Method ◽  
Road Capacity ◽  
Empirical Bayes Method ◽  
Safety Effect

Hard shoulder running (HSR) has been increasingly used as a sustainable and viable way to increase road capacity. This study investigated the safety effect of HSR on freeways in South Korea using the empirical Bayes method. This study found an increase in the total number of crashes. In terms of crash severity, a higher proportion of crashes (25.3%) on 2(3)-lane sections were found to be serious (involving injuries and/or fatalities) compared to those on 4(5)-lane sections (3.6%). Also, a positive relationship was found between the length of the hard shoulder running and changes in crash frequencies. Thus, hard shoulder running on lengthy 2(3)-lane freeways should be avoided.

AN EMPIRICAL BAYES METHOD FOR STUDYING VARIATION IN KNEE REPLACEMENT RATES

1996 ◽  
Vol 15 (17) ◽  
pp. 1875-1884 ◽  
Author(s):  
XIAO-HUA ZHOU ◽  
B. P. KATZ ◽  
E. HOLLEMAN ◽  
C. A. MELFI ◽  
R. DITTUS
Keyword(s):  
Knee Replacement ◽  
Empirical Bayes ◽  
Bayes Method ◽  
Empirical Bayes Method

Weighted Analysis of Paired Microarray Experiments

2005 ◽  
Vol 4 (1) ◽  
Author(s):  
Erik Kristiansson ◽  
Anders Sjögren ◽  
Mats Rudemo ◽  
Olle Nerman
Keyword(s):  
Empirical Bayes ◽  
Mixed Type ◽  
Simulated Data ◽  
Analysis Method ◽  
Bayes Method ◽  
Microarray Experiments ◽  
The Third ◽  
Weighted Analysis ◽  
Empirical Bayes Method ◽  
Before And After

In microarray experiments quality often varies, for example between samples and between arrays. The need for quality control is therefore strong. A statistical model and a corresponding analysis method is suggested for experiments with pairing, including designs with individuals observed before and after treatment and many experiments with two-colour spotted arrays. The model is of mixed type with some parameters estimated by an empirical Bayes method. Differences in quality are modelled by individual variances and correlations between repetitions. The method is applied to three real and several simulated datasets. Two of the real datasets are of Affymetrix type with patients profiled before and after treatment, and the third dataset is of two-colour spotted cDNA type. In all cases, the patients or arrays had different estimated variances, leading to distinctly unequal weights in the analysis. We suggest also plots which illustrate the variances and correlations that affect the weights computed by our analysis method. For simulated data the improvement relative to previously published methods without weighting is shown to be substantial.

Sign in / Sign up

Export Citation Format

Share Document