Two‐part regression models are frequently used to analyze longitudinal count data with
excess zeros, where the same set of subjects is repeatedly observed over time. In this …

Abstract Analysis of longitudinal data with excessive zeros has gained increasing attention
in recent years; however, current approaches to the analysis of longitudinal data with …

Count data are collected repeatedly over time in many applications, such as biology,
epidemiology, and public health. Such data are often characterized by the following three …

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 …

Two‐part models are quite well established in the economic literature, since they resemble
accurately a principal‐agent type model, where homogeneous, observable, counted …

Conventional pattern‐mixture models can be highly sensitive to model misspecification. In
many longitudinal studies, where the nature of the drop‐out and the form of the population …

Several applications involving counts present a large proportion of zeros (excess-of-zeros
data). A popular model for such data is the hurdle model, which explicitly models the …

In medical and health studies, heterogeneities in clustered count data have been
traditionally modeled by positive random effects in Poisson mixed models; however …

Background Within longitudinal epidemiological research,'count'outcome variables with an
excess of zeros frequently occur. Although these outcomes are frequently analysed with a …

We describe a mixed-effect hurdle model for zero-inflated longitudinal count data, where a
baseline variable is included in the model specification. Association between the count data …