Use of Empirical Bayesian Methods to Estimate Crash Modification Factors for Daytime versus Nighttime Work Zones

2011 ◽  
Vol 2241 (1) ◽  
pp. 29-38 ◽  
Author(s):  
Raghavan Srinivasan ◽  
Gerald Ullman ◽  
Melisa Finley ◽  
Forrest Council
Keyword(s):  
Bayesian Methods ◽  
Work Zones ◽  
Empirical Bayesian ◽  
Crash Modification Factors

Development of Crash Modification Factors for Uncontrolled Pedestrian Crossing Treatments

2017 ◽  
Vol 2636 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Charlie Zegeer ◽  
Craig Lyon ◽  
Raghavan Srinivasan ◽  
Bhagwant Persaud ◽  
Bo Lan ◽  
...  
Keyword(s):  
The United States ◽  
Crash Risk ◽  
Limited Sample ◽  
Cross Sectional ◽  
Empirical Bayesian ◽  
Treatment Type ◽  
Crash Modification Factors ◽  
Pedestrian Crashes ◽  
Pedestrian Crossing ◽  
Crash Types

The objective of this study was to develop crash modification factors for four treatment types: rectangular rapid-flashing beacon (RRFB), pedestrian hybrid beacon (PHB), pedestrian refuge island (RI), and advance yield or stop markings and signs (AS). From 14 cities throughout the United States, 975 treatment and comparison sites were selected. Most of the treatment sites were selected at intersections on urban, multilane streets, because these locations present a high risk for pedestrian crashes and are where countermeasures typically are needed most. For each treatment site, relevant data were collected on the treatment characteristics, traffic, geometric, and roadway variables, and the pedestrian crashes and other crash types that occurred at each site. Cross-sectional regression models and before–after empirical Bayesian analysis techniques were used to determine the crash effects of each treatment type. All four of the treatment types were found to be associated with reductions in pedestrian crash risk, compared with the reductions at untreated sites. PHBs were associated with the greatest reduction of pedestrian crash risk (55% reduction), followed by RRFBs (47% reduction), RIs (32% reduction), and AS (25% reduction). The results for RRFBs had their basis in a limited sample and must be used with caution.

SPATIAL DISTRIBUTION OF NEW CASES OF TUBERCULOSIS IN THE STATE OF RIO GRANDE DO NORTE, BRAZIL.

2014 ◽  
Vol 37 (2) ◽  
pp. 452
Author(s):  
Isabelle Ribeiro Barbosa
Keyword(s):  
Spatial Distribution ◽  
Bayesian Methods ◽  
Rio Grande ◽  
The State ◽  
Ecological Analysis ◽  
Empirical Bayesian ◽  
Low Incidence ◽  
Global And Local

This study presents the results of an ecological analysis of the spatial distribution of 4,739 new cases of tuberculosis in Rio Grande do Norte, Brazil, between 2006 and 2010. Global and Local empirical Bayesian methods were used in the analysis. Tuberculosis was found to be homogenously distributed and present at low incidence; additionally, incidence was underestimated in 17.96% of the municipalities. 

Empirical Bayesian Methods for Archaeological Survey Data: An Application from the Mesa Verde Region

2007 ◽  
Vol 72 (2) ◽  
pp. 241-272 ◽  
Author(s):  
Scott G. Ortman ◽  
Mark D. Varien ◽  
T. Lee Gripp
Keyword(s):  
Survey Data ◽  
Bayesian Methods ◽  
Ad Hoc ◽  
Archaeological Site ◽  
Archaeological Survey ◽  
Empirical Bayesian ◽  
Ancestral Pueblo ◽  
History Of ◽  
The Rich ◽  
The Relationship

Cultural resource databases represent the single largest compilations of archaeological site data, but these databases are seldom used in research because they were designed for management purposes, evolved from paper-based inventories, contain significant interobserver variation, and record information inconsistently. In this paper we present methods designed to alleviate these problems in an analysis of more than 3,000 ancestral Pueblo habitation sites from southwestern Colorado. Our methods draw heavily upon Bayesian statistical concepts and utilize the rich excavation records of our study area to quantify the relationship between surface evidence and excavation results using probabilities. This approach offers a number of advantages over ad hoc, judgmental approaches, and produces a more empirically justified history of ancestral Pueblo settlement in our study area. We believe methods like these have great potential for reconstructing settlement patterns from survey data.

Spatial and Multivariate Analysis, Random Sampling Error, and Analytical Noise: Empirical Bayesian Methods at Teotihuacan, Mexico

1999 ◽  
Vol 64 (1) ◽  
pp. 137-152 ◽  
Author(s):  
Ian G. Robertson
Keyword(s):  
Multivariate Analysis ◽  
Bayesian Methods ◽  
Random Sampling ◽  
Sampling Error ◽  
Behavioral Variability ◽  
Empirical Bayesian ◽  
Different Types ◽  
Exploratory Multivariate Analysis ◽  
Teotihuacan Mexico ◽  
Artifact Type

Methods of empirical Bayesian statistical inference can help archaeologists deal with problems inherent in variably-sized and, particularly, small artifact samples. The desirability of systematically controlling random effects of sampling error when mapping estimates of artifact type proportions is emphasized in this paper, and concrete examples are provided using ceramic data from the Central Mexican city of Teotihuacan. A Bayesian approach also may be beneficial for pretreating data destined for other kinds of quantitative analysis, such as exploratory multivariate analysis. Correspondence analysis using observed proportions of different types of pottery in assemblages pertaining to the Xolalpan and Metepec phases produces vague results that suggest little in the way of interpretable structure. However, a parallel analysis using posterior estimates of proportions reveals meaningful associations of ceramic categories that appear to relate to more general dimensions of behavioral variability.

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