Discrete-time semi-Markov modeling of human papillomavirus persistence

C. E. Mitchell, M. G. Hudgens, C. C. King, S. Cu-Uvin, Y. Lo, A. Rompalo, J. Sobel, J. S. Smith

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)2160-2170
Number of pages11
JournalStatistics in Medicine
Issue number17
StatePublished - Jul 30 2011


  • Panel data
  • Stochastic process

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability


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