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Two-Part and Related Regression Models for Longitudinal Data

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...

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Autores principales: Farewell, V.T., Long, D.L., Tom, B.D.M., Yiu, S., Su, L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5590716/
https://www.ncbi.nlm.nih.gov/pubmed/28890906
http://dx.doi.org/10.1146/annurev-statistics-060116-054131
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author Farewell, V.T.
Long, D.L.
Tom, B.D.M.
Yiu, S.
Su, L.
author_facet Farewell, V.T.
Long, D.L.
Tom, B.D.M.
Yiu, S.
Su, L.
author_sort Farewell, V.T.
collection PubMed
description 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.
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spelling pubmed-55907162017-09-08 Two-Part and Related Regression Models for Longitudinal Data Farewell, V.T. Long, D.L. Tom, B.D.M. Yiu, S. Su, L. Annu Rev Stat Appl Article 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. 2017-03 /pmc/articles/PMC5590716/ /pubmed/28890906 http://dx.doi.org/10.1146/annurev-statistics-060116-054131 Text en https://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See credit lines of images or other third party material in this article for license information.
spellingShingle Article
Farewell, V.T.
Long, D.L.
Tom, B.D.M.
Yiu, S.
Su, L.
Two-Part and Related Regression Models for Longitudinal Data
title Two-Part and Related Regression Models for Longitudinal Data
title_full Two-Part and Related Regression Models for Longitudinal Data
title_fullStr Two-Part and Related Regression Models for Longitudinal Data
title_full_unstemmed Two-Part and Related Regression Models for Longitudinal Data
title_short Two-Part and Related Regression Models for Longitudinal Data
title_sort two-part and related regression models for longitudinal data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5590716/
https://www.ncbi.nlm.nih.gov/pubmed/28890906
http://dx.doi.org/10.1146/annurev-statistics-060116-054131
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