A mixture model with Poisson and zero-truncated Poisson components to analyze road traffic accidents in Turkey.

ABSTRACT: The analysis of traffic accident data is crucial to address numerous concerns, such as understanding contributing factors in an accident's chain-of-events, identifying hotspots, and informing policy decisions about road safety management. The majority of statistical models employed for analyzing traffic accident data are logically count regression models (commonly Poisson regression) since a count - like the number of accidents - is used as the response. However, features of the observed data frequently do not make the Poisson distribution a tenable assumption. For example, observed data rarely demonstrate an equal mean and variance and often times possess excess zeros. Sometimes, data may have heterogeneous structure consisting of a mixture of populations, rather than a single population.

SUBMITTER: Unlu HK 

PROVIDER: S-EPMC9042158 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature