Utilizing alternate models for analyzing count outcomes - Rydberg, Jason (Crime & delinquency, 2017)
Although ordinary least squares (OLS) regression was once a common tool for modeling discrete count outcomes in criminology and criminal justice, the past several decades have seen an increasing reliance on regression techniques specifically designed for such purposes. Utilizing a practical example from the 1958 Philadelphia Birth Cohort, this article describes and compares various estimation strategies for modeling such outcome variables, including a discussion of the inappropriateness of OLS for such purposes and specific features of discrete count distributions that complicate statistical inference—overdispersion, non-independence, and excess zeros. Practical advice for selecting an appropriate modeling strategy is offered.