No Zero Left Behind: Comparing the Fit for Zero-Inflation Models as a Function of Skew and Proportion of Zeros

by Jeffrey M. Miller, M. David Miller.

Abstract: Several models have been proposed for analyzing data characterized by a preponderance of zeros. Substantively, the choice between these models should be based solely on the data generating process. However, datasets can vary as a function of both the proportions of zeros and the distribution for the nonzeros. A Monte Carlo design was used to sample 1,000 cases from each of six distributions and five proportions of zeros. Between-model superiority was tested using deviance statistics and AICs over 2,000 simulations per condition. The results suggest that the best-fitting zero-inflated model sometimes depends on the proportion of zeros and the distribution for the nonzeros. In fact, there are situations where the zero-inflated models are not necessary.

Key Words: Zero-Inflation, ZIP, Hurdle, Zero-Inflated Poisson, Poisson

Jeffrey M. Miller,
M. David Miller,

Editor: Joseph W. McKean,

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