Analysis of Crash Data Using Quantile Regression for Counts

AbstractStatistical models that describe the relationship between crash frequency and its influencing factors have been widely studied for the last three decades. Most of the existing methodologies use these models with count data and their variants to study the mean effects of covariates on crash frequency. This study seeks to explore the use of quantile regression for counts as a methodological alternative in analyzing crash frequency. Compared with existing models, the proposed model provides a fuller and more robust analysis of crash data for at least two reasons. First, crash data usually follow typical count distributions with a large proportion of zeros, and the remaining values highly skew toward the right. This nature of crash data makes quantile regression appealing because it can provide more comprehensive information about the effects of covariates on crash frequency rather than just the mean because quantile regression allows various quantiles of a population to be estimated. Second, as a sem...

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