title: Fitting semiparametric regressions for panel count survival data with an R package spef.
abstract: Observing recurrent event processes at discrete, possibly random times produces panel count data. Modeling panel count data is challenging because the event process may be associated with the observation pattern and censoring time. Various methods have been proposed to fit flexible semiparametric regression models, but no software is available to practitioners. We develop an R package spef that fits semiparametric regression models for panel count data. Existing methods in the literature are implemented as well as our recently developed estimating equations approach. Some of the implemented methods allow informative observation and censoring scheme. The package usage is illustrated with a well-known bladder tumor data set.
authors.affiliation: Department of Statistics, University of Connecticut, 215 Glenbrook Rd., U-4120, Storrs, CT 06269, USA. wangxj03@gmail.com
authors.forename: Xiaojing
authors.initials: X
authors.lastname: Wang
authors.forename: Jun
authors.initials: J
authors.lastname: Yan
mesh_terms: D006801:Humans; D016013:Likelihood Functions; D012044:Regression Analysis; D016019:Survival Analysis; D001749:Urinary Bladder Neoplasms / Q000473:pathology*