Chiou, Sy HanHuang, C. -YXu, G.Yan, J.2019-11-082019-11-082018-06-130306-7734https://hdl.handle.net/10735.1/7101Full text access from Treasures at UT Dallas is restricted to current UTD affiliates (use the provided Link to Article).Panel 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 Instituteen©2018 The Authors and the International Statistical Institute.CountingGeneralized estimating equationsRecurrent eventsRegression analysisSkin--CancerarticleChiou, 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.12271871