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Title: Modeling count data with excess zeroes, an empirical application to traffic accidents
Authors: Chin, Hoong Chor
Quddus, Mohammed A.
Keywords: Traffic accidents
Zero-inflated models
Poisson regression
Negative binomial regression
Issue Date: 2003
Publisher: © SAGE Publications Ltd
Citation: CHIN, H.C. and QUDDUS, M.A., 2003. Modeling count data with excess zeroes, an empirical application to traffic accidents. Sociological Methods & Research, 31(4), pp. 90-116.
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 nonzero- 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.
Description: This article is Closed Access. It was published in the journal, Sociological Methods & Research [© Sage] and is available at: http://dx.doi.org/10.1177/0049124103253459
Version: Closed Access
DOI: 10.1177/0049124103253459
URI: https://dspace.lboro.ac.uk/2134/4866
ISSN: 0049-1241
Appears in Collections:Closed Access (Civil and Building Engineering)

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