Two-Part and Related Regression Models for Longitudinal Data

Annu Rev Stat Appl. 2017 Mar:4:283-315. doi: 10.1146/annurev-statistics-060116-054131.

Abstract

Statistical models that involve a two-part mixture distribution are applicable in a variety of situations. Frequently, the two parts are a model for the binary response variable and a model for the outcome variable that is conditioned on the binary response. Two common examples are zero-inflated or hurdle models for count data and two-part models for semicontinuous data. Recently, there has been particular interest in the use of these models for the analysis of repeated measures of an outcome variable over time. The aim of this review is to consider motivations for the use of such models in this context and to highlight the central issues that arise with their use. We examine two-part models for semicontinuous and zero-heavy count data, and we also consider models for count data with a two-part random effects distribution.

Keywords: longitudinal data; marginal covariate effects; mixture distributions; random effects; two-part models.