Modeling Count Data with Excess Zeroes

Author:

Chin Hoong Chor1,Quddus Mohammed Abdul2

Affiliation:

1. National University of Singapore

2. Imperial College, London

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.

Publisher

SAGE Publications

Subject

Sociology and Political Science,Social Sciences (miscellaneous)

Reference25 articles.

1. Barron, David N. 1998. “The Analysis of Count Data: Overdispersion and Autocorrelation.” Sociological Methodology 22:179-219.

2. Berndt, E. R., B. H. Hall, R. E. Hall, and J. A. Hausman. 1974. “Estimation and Inference in Non-Linear Structural Models. Annals of Economic and Social Measurement 3:653-665.

3. Econometric models based on count data. Comparisons and applications of some estimators and tests

4. Gurmu, S. and P. K. Trivedi. 1996. “Excess Zeroes in Count Models for Recreational Trips.” Journal of Business and Economic Statistics 14:469-477.

5. Selection of the Best Subset in Regression Analysis

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