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Generalized Linear Model for Automobile Fatality Rate Prediction in R

Generalized Linear Model for Automobile Fatality Rate Prediction in R

Gao Niu, Alan Olinsky
Copyright: © 2020 |Pages: 25
ISBN13: 9781799827689|ISBN10: 1799827682|ISBN13 Softcover: 9781799827696|EISBN13: 9781799827702
DOI: 10.4018/978-1-7998-2768-9.ch005
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MLA

Niu, Gao, and Alan Olinsky. "Generalized Linear Model for Automobile Fatality Rate Prediction in R." Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities, edited by Richard S. Segall and Gao Niu, IGI Global, 2020, pp. 137-161. https://doi.org/10.4018/978-1-7998-2768-9.ch005

APA

Niu, G. & Olinsky, A. (2020). Generalized Linear Model for Automobile Fatality Rate Prediction in R. In R. Segall & G. Niu (Eds.), Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities (pp. 137-161). IGI Global. https://doi.org/10.4018/978-1-7998-2768-9.ch005

Chicago

Niu, Gao, and Alan Olinsky. "Generalized Linear Model for Automobile Fatality Rate Prediction in R." In Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities, edited by Richard S. Segall and Gao Niu, 137-161. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-7998-2768-9.ch005

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Abstract

This chapter demonstrates the descriptive and statistical modeling function in R. The automobile fatal accident data of the United States is extracted from the Fatality Analysis Reporting System (FARS). The model will be used to understand significant contributing factors of automobile accident death when a fatal crash happens. First, descriptive analysis is performed by basic R functions and packages. Then, generalized linear model (GLM) with logit link function is explored and constructed. Finally, multiple validation metrics are introduced and calculated to ensure the reasonability and accuracy of the predictions. The focus of this chapter is to demonstrate the power and flexibility of the most popular Open Source Statistical Software (OSSS) through a real data analysis.

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