Power analysis for zero-inflated Poisson and negative binomial generalized linear models using Monte Carlo simulation

Many research fields involve count data with zero inflation. A commonly chosen model for analysing a relationship between predictors and a response variable in these scenarios is a zero-inflated generalized linear model (GLM). This model is a mixture of a count-based GLM and a zero-inflation component, with a mixing proportion that determines the amount of excess zeroes. As the use of zero-inflated count models is rising, it is important to be able to conduct a power analysis to properly design studies with such models. In this paper, we propose a flexible method for power analysis with zero-inflated count models using Monte Carlo simulation. We have created the R package ZIPowerAnalysis, which can be used to easily conduct a power analysis for any designed study that will incorporate a zero-inflated count GLM.