Please use this identifier to cite or link to this item: https://doi.org/10.1177/0049124103253459
Title: Modeling count data with excess zeroes: An empirical application to traffic accidents
Authors: Chin, H.C. 
Quddus, M.A.
Keywords: Negative binomial regression
Poisson regression
Traffic accidents
Zero-inflated models
Issue Date: Aug-2003
Source: Chin, H.C., Quddus, M.A. (2003-08). Modeling count data with excess zeroes: An empirical application to traffic accidents. Sociological Methods and Research 32 (1) : 90-116. ScholarBank@NUS Repository. https://doi.org/10.1177/0049124103253459
Abstract: There are many studies in social sciences, such as traffic accident analysis, in which the event counts may be characterized by a large number of zero observations. In this article, a proposed model that takes into account both the zero-count state and the non-zero-count state is used to describe the traffic accident phenomenon. The probability of the zero-count state (p) and the mean number of event counts (μ) in the non-zero-count state may depend on the covariates. Sometimes, p and μ, are unrelated, while at other times, p may assume a simple function of μ. In proposing the model, different types of traffic accidents at signalized Intersections in Singapore were investigated. The results demonstrate that the zero-altered probability process is an appropriate technique for modeling specific types of accidents in which the data contain many zero counts.
Source Title: Sociological Methods and Research
URI: http://scholarbank.nus.edu.sg/handle/10635/65826
ISSN: 00491241
DOI: 10.1177/0049124103253459
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