Semiparametric Regression Analysis of Panel Count Data: A Practical Review

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dc.contributor.ORCID0000-0003-2672-662X (Chiou, SH)
dc.contributor.authorChiou, Sy Han
dc.contributor.authorHuang, C. -Y
dc.contributor.authorXu, G.
dc.contributor.authorYan, J.
dc.contributor.utdAuthorChiou, Sy Han
dc.date.accessioned2019-11-08T21:55:20Z
dc.date.available2019-11-08T21:55:20Z
dc.date.created2018-06-13
dc.descriptionFull text access from Treasures at UT Dallas is restricted to current UTD affiliates (use the provided Link to Article).
dc.description.abstractPanel count data arise in many applications when the event history of a recurrent event process is only examined at a sequence of discrete time points. In spite of the recent methodological developments, the availability of their software implementations has been rather limited. Focusing on a practical setting where the effects of some time-independent covariates on the recurrent events are of primary interest, we review semiparametric regression modelling approaches for panel count data that have been implemented in R package spef. The methods are grouped into two categories depending on whether the examination times are associated with the recurrent event process after conditioning on covariates. The reviewed methods are illustrated with a subset of the data from a skin cancer clinical trial. © 2018 The Authors and the International Statistical Institute
dc.description.departmentSchool of Natural Sciences and Mathematics
dc.identifier.bibliographicCitationChiou, S. H., C. -Y Huang, G. Xu, and J. Yan. 2019. "Semiparametric Regression Analysis of Panel Count Data: A Practical Review." International Statistical Review 87(1): 24-43, doi: 10.1111/insr.12271
dc.identifier.issn0306-7734
dc.identifier.issue1
dc.identifier.urihttps://hdl.handle.net/10735.1/7101
dc.identifier.volume87
dc.language.isoen
dc.publisherJohn Wiley and Sons Ltd.
dc.relation.urihttps://dx.doi.org/10.1111/insr.12271
dc.rights©2018 The Authors and the International Statistical Institute.
dc.source.journalInternational Statistical Review
dc.subjectCounting
dc.subjectGeneralized estimating equations
dc.subjectRecurrent events
dc.subjectRegression analysis
dc.subjectSkin--Cancer
dc.titleSemiparametric Regression Analysis of Panel Count Data: A Practical Review
dc.type.genrearticle

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