Modeling count data with excess zeroes - An empirical application to traffic accidents

被引:40
作者
Chin, HC
Quddus, MA
机构
[1] Natl Univ Singapore, Dept Civil Engn, Singapore 117548, Singapore
[2] Univ London Imperial Coll Sci Technol & Med, London SW7 2AZ, England
关键词
traffic accidents; zero-inflated models; Poisson regression; negative binomial regression;
D O I
10.1177/0049124103253459
中图分类号
O1 [数学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 0701 ; 070101 ;
摘要
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 (mu) in the non-zero-count state may depend on the covariates. Sometimes, p and mu are unrelated, while at other times, p may assume a simple function of A. 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.
引用
收藏
页码:90 / 116
页数:27
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