Modeling Heaped Count Data

Abstract

We present motivation and new commands for modeling heaped count data. These data may appear when subjects report counts that are rounded or favor multiples (digit preference) of a certain outcome, such as the number of cigarettes reported. The new commands for fitting count regression models (Poisson, generalized Poisson, negative binomial) are also accompanied by real-world examples comparing the heaped regression model with the usual regression model as well as the heaped zero-inflated model with the usual zero-inflated model.