ArticleStatistics in medicine2011
Discrete-time semi-Markov modeling of human papillomavirus persistence.
Article in Statistics in medicine, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- A joint model of persistent human papillomavirus infection and cervical cancer risk: Implications for cervical cancer screening.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2015Article
- Analysis of longitudinal multivariate outcome data from couples cohort studies: application to HPV transmission dynamics.Journal of the American Statistical Association · 2015Article
- Key considerations and current perspectives of epidemiological studies on human papillomavirus persistence, the intermediate phenotype to cervical cancer.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2013Article
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Authors and funding
8 authors.
Funding
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.
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