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Two-Part and Related Regression Models for Longitudinal Data.

Published version
Peer-reviewed

Type

Article

Change log

Authors

Farewell, VT 
Long, DL 
Tom, BDM 
Yiu, S 

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.

Description

Keywords

longitudinal data, marginal covariate effects, mixture distributions, random effects, two-part models

Journal Title

Annual Review of Statistics and Its Application

Conference Name

Journal ISSN

2326-8298
2326-831X

Volume Title

4

Publisher

Annual Reviews Inc.
Sponsorship
MRC (unknown)
Medical Research Council (MR/M025152/1)
The authors acknowledge the following funding sources: MRC funding U015261167, MC\_UP\_1302/3, and National Institutes of Health (NIH) grant U54GM104942 (NIGMS).