Modelling zero-inflated count data when exposure varies: with an application to sick leave

Abstract

This paper is concerned with the analysis of zero-inflated count data when time of exposure varies. It proposes a new zero-inflated count data model that is based on two homogeneous Poisson processes and accounts for exposure time in a theory consistent way. The new model is used in an application to the effect of insurance generosity on the number of absent days.Exposure, Poisson regression, complementary log-log link