title: Discrete-time semi-Markov modeling of human papillomavirus persistence.
abstract: Multi-state modeling is often employed to describe the progression of a disease process. In epidemiological studies of certain diseases, the disease state is typically only observed at periodic clinical visits, producing incomplete longitudinal data. In this paper we consider fitting semi-Markov models to estimate the persistence of human papillomavirus (HPV) type-specific infection in studies where the status of HPV type(s) is assessed periodically. Simulation study results are presented indicating that the semi-Markov estimator is more accurate than an estimator currently used in the HPV literature. The methods are illustrated using data from the HIV Epidemiology Research Study.
authors.affiliation: Department of Biostatistics, The University of North Carolina, Chapel Hill, NC 27599, USA.
authors.forename: C E
authors.initials: CE
authors.lastname: Mitchell
authors.forename: M G
authors.initials: MG
authors.lastname: Hudgens
authors.forename: C C
authors.initials: CC
authors.lastname: King
authors.forename: S
authors.initials: S
authors.lastname: Cu-Uvin
authors.forename: Y
authors.initials: Y
authors.lastname: Lo
authors.forename: A
authors.initials: A
authors.lastname: Rompalo
authors.forename: J
authors.initials: J
authors.lastname: Sobel
authors.forename: J S
authors.initials: JS
authors.lastname: Smith
mesh_terms: D003198:Computer Simulation; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008390:Markov Chains; D018448:Models, Immunological; D027383:Papillomaviridae / Q000276:immunology*; D030361:Papillomavirus Infections / Q000453:epidemiology / Q000276:immunology* / Q000821:virology*