The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives

2010 ◽  
Vol 44 (5) ◽  
pp. 291-305 ◽  
Author(s):  
Dominique Lord ◽  
Fred Mannering
Keyword(s):  
Statistical Analysis ◽  
Frequency Data ◽  
Crash Frequency

Was This in Your Statistics Textbook? IV. Frequency Data

1989 ◽  
Vol 25 (1) ◽  
pp. 11-25
Author(s):  
D. J. Finney
Keyword(s):  
Statistical Analysis ◽  
Contingency Tables ◽  
The Other ◽  
Frequency Data ◽  
Significance Tests ◽  
Test Statistic ◽  
Jumping To Conclusions ◽  
Proper Role ◽  
Measure Of Association

SUMMARYObservations that are frequencies rather than measurements often call for special types of statistical analysis. This paper comments on circumstances in which methods for one type of data can sensibly be used for the other. A section on two-way contingency tables emphasizes the proper role of χ2 a test statistic but not a measure of association; it mentions the distinction between one-tail and two-tail significance tests and reminds the reader of dangers. Multiway tables bring new complications, and the problems of interactions when additional classificatory factors are explicit or hidden are discussed at some length. A brief outline attempts to show how probit, logit, and similar techniques are related to the analysis of contingency tables. Finally, three unusual examples are described as illustrations of the care that is needed to avoid jumping to conclusions on how frequency data should be analysed.

scholarly journals A Statistical Analysis Of CoV-19 Positive Test Frequency Data Indicates A Need For Greater Attention To CoV-19 Test Quality And Pre-Wuhan Cov-19 Prevalence

2020 ◽  
Author(s):  
James L. Sherley
Keyword(s):  
Statistical Analysis ◽  
Epidemiological Data ◽  
Positive Test ◽  
Human Populations ◽  
Frequency Data ◽  
Test Frequency ◽  
Test Quality ◽  
Public Response ◽  
History Of ◽  
Improved Accuracy

AbstractIncreased attention to analysis of SARS-CoV-2 (CoV-19) positive test frequency data is essential for achievement of better knowledge of the natural history of the virus in human populations, improved accuracy of CoV-19 epidemiological data, and development of public response policies that are better crafted to address the current CoV-19-induced global crisis. A statistical analysis of currently available positive test frequency data reveals a surprisingly uniform relationship between the number of CoV-19 test performed and the number of positive tests obtained. The uniformity is particularly striking for United States CoV-19 test data. Such observations warrant closer evaluation of other factors, besides virus spread, that may also contribute to the nature of the coronavirus pandemic. These include indigenous CoV-19 and the quality of CoV-19 testing.

Seabed characterization from statistical analysis of high‐frequency data

2001 ◽  
Vol 110 (5) ◽  
pp. 2661-2661
Author(s):  
Samantha J. Dugelay ◽  
Richard J. Brothers ◽  
Gary J. Heald
Keyword(s):  
Statistical Analysis ◽  
High Frequency ◽  
High Frequency Data ◽  
Frequency Data

scholarly journals Investigating Spatial Autocorrelation and Spillover Effects in Freeway Crash-Frequency Data

2019 ◽  
Vol 16 (2) ◽  
pp. 219 ◽  
Author(s):  
Huiying Wen ◽  
Xuan Zhang ◽  
Qiang Zeng ◽  
Jaeyoung Lee ◽  
Quan Yuan
Keyword(s):  
Spatial Autocorrelation ◽  
Hybrid Model ◽  
Traffic Safety ◽  
Spillover Effects ◽  
Spatial Effects ◽  
Frequency Data ◽  
Contributing Factors ◽  
Exogenous Variables ◽  
Crash Frequency ◽  
Adjacent Segments

This study attempts to investigate spatial autocorrelation and spillover effects in micro traffic safety analysis. To achieve the objective, a Poisson-based count regression with consideration of these spatial effects is proposed for modeling crash frequency on freeway segments. In the proposed hybrid model, the spatial autocorrelation and the spillover effects are formulated as the conditional autoregressive (CAR) prior and the exogenous variables of adjacent segments, respectively. The proposed model is demonstrated and compared to the models with only one kind of spatial effect, using one-year crash data collected from Kaiyang Freeway, China. The results of Bayesian estimation conducted in WinBUGS show that significant spatial autocorrelation and spillover effects simultaneously exist in the freeway crash-frequency data. The lower value of deviance information criterion (DIC) and more significant exogenous variables for the hybrid model compared to the other alternatives, indicate the strength of accounting for both spatial autocorrelation and spillover effects on improving model fit and identifying crash contributing factors. Moreover, the model results highlight the importance of daily vehicle kilometers traveled, and horizontal and vertical alignments of targeted segments and adjacent segments on freeway crash occurrences.

Application of the Poisson-Tweedie distribution in analyzing crash frequency data

2020 ◽  
Vol 137 ◽  
pp. 105456 ◽  
Author(s):  
Dibakar Saha ◽  
Priyanka Alluri ◽  
Eric Dumbaugh ◽  
Albert Gan
Keyword(s):  
Frequency Data ◽  
Crash Frequency ◽  
Tweedie Distribution
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