A study of the score test in discrimination poisson and zero-inflated poisson models

Abstract

In many experimental situations the sample may present excess zero observations and generally are used probabilistic models for zero inflated to represent them. However no one knows precisely the amount of zero observations that these models support. Depending on the sample size and null observations number the Poisson model can be used. Based on this question, the objective of this paper is to evaluate the properties of Type I error and power of the score test (proposed by Van Den Broek (1995) to discriminate the Poisson and Zero-inflated Poisson models) and ascertain the most appropriate model to represent a sample with excess zeros without compromising the statistical inference. Through Monte Carlo simulation we concluded that when considering a sample of size at least n = 40 with 30% of the null observations, the score test had a high discriminatory power between the ZIP and Poisson model indicating that in fact is relevant the use of the ZIP model.