Zero-inflated models for adjusting varying exposures: a cautionary note on the pitfalls of using offset.

ABSTRACT: Zero-inflated count data are frequently encountered in public health and epidemiology research. Two-parts model is often used to model the excessive zeros, which are a mixture of two components: a point mass at zero and a count distribution, such as a Poisson distribution. When the rate of events per unit exposure is of interest, offset is commonly used to account for the varying extent of exposure, which is essentially a predictor whose regression coefficient is fixed at one. Such an assumption of exposure effect is, however, quite restrictive for many practical problems. Further, for zero-inflated models, offset is often only included in the count component of the model. However, the probability of excessive zero component could also be affected by the amount of 'exposure'. We, therefore

SUBMITTER: Feng C 

PROVIDER: S-EPMC9042155 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature