Discrete-time semi-Markov modeling of human papillomavirus persistence
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 mod...
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| Veröffentlicht in: | Statistics in medicine 2011-07, Vol.30 (17), p.2160-2170 |
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| container_title | Statistics in medicine |
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| creator | Mitchell, C. E. Hudgens, M. G. King, C. C. Cu-Uvin, S. Lo, Y. Rompalo, A. Sobel, J. Smith, J. S. |
| description | 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. Copyright © 2011 John Wiley & Sons, Ltd. |
| doi_str_mv | 10.1002/sim.4257 |
| format | Article |
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E.</creatorcontrib><creatorcontrib>Hudgens, M. G.</creatorcontrib><creatorcontrib>King, C. C.</creatorcontrib><creatorcontrib>Cu-Uvin, S.</creatorcontrib><creatorcontrib>Lo, Y.</creatorcontrib><creatorcontrib>Rompalo, A.</creatorcontrib><creatorcontrib>Sobel, J.</creatorcontrib><creatorcontrib>Smith, J. S.</creatorcontrib><title>Discrete-time semi-Markov modeling of human papillomavirus persistence</title><title>Statistics in medicine</title><addtitle>Statist. Med</addtitle><description>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. Copyright © 2011 John Wiley & Sons, Ltd.</description><subject>Computer Simulation</subject><subject>Epidemiology</subject><subject>Estimating techniques</subject><subject>Female</subject><subject>Human immunodeficiency virus</subject><subject>Human papillomavirus</subject><subject>Humans</subject><subject>Longitudinal Studies</subject><subject>Markov analysis</subject><subject>Markov Chains</subject><subject>Models, Immunological</subject><subject>panel data</subject><subject>Papillomaviridae - immunology</subject><subject>Papillomavirus Infections - epidemiology</subject><subject>Papillomavirus Infections - immunology</subject><subject>Papillomavirus Infections - virology</subject><subject>Simulation</subject><subject>stochastic process</subject><issn>0277-6715</issn><issn>1097-0258</issn><issn>1097-0258</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kV1PFDEUQBsjkRVM_AVm4ou8DPZjOm1fTAwCSwJLVAyPTbdzB4rT6djOrPLv7YZl_Uj06T705OT2HoReEnxIMKZvk_OHFeXiCZoRrESJKZdP0QxTIcpaEL6Lnqd0hzEhnIpnaJcSzqSSfIZOPrhkI4xQjs5DkcC78sLEr2FV-NBA5_qbIrTF7eRNXwxmcF0XvFm5OKVigJhcGqG3sI92WtMleLGZe-jLyfHV0bw8vzw9O3p_XlqO8y7Alm1tW8WEbQgjZEnNsmoUqw0RUrWWGmYZoxbXzFKumrbCOI8Gi8owYy3bQ-8evMO09NBY6MdoOj1E502818E4_edL7271TVhpRqiqapUFbzaCGL5NkEbt8wGg60wPYUpaikpmUIpMHvyXJJhiyVReNaOv_0LvwhT7fIjsq7GURLBfPhtDShHa7dYE63VFnSvqdcWMvvr9l1vwMVsGygfgu-vg_p8i_fnsYiPc8OtcP7Z87qxrwQTX14tTvbi6nn_8NF_omv0Efia2RQ</recordid><startdate>20110730</startdate><enddate>20110730</enddate><creator>Mitchell, C. 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S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Discrete-time semi-Markov modeling of human papillomavirus persistence</atitle><jtitle>Statistics in medicine</jtitle><addtitle>Statist. Med</addtitle><date>2011-07-30</date><risdate>2011</risdate><volume>30</volume><issue>17</issue><spage>2160</spage><epage>2170</epage><pages>2160-2170</pages><issn>0277-6715</issn><issn>1097-0258</issn><eissn>1097-0258</eissn><coden>SMEDDA</coden><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. 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| subjects | Computer Simulation Epidemiology Estimating techniques Female Human immunodeficiency virus Human papillomavirus Humans Longitudinal Studies Markov analysis Markov Chains Models, Immunological panel data Papillomaviridae - immunology Papillomavirus Infections - epidemiology Papillomavirus Infections - immunology Papillomavirus Infections - virology Simulation stochastic process |
| title | Discrete-time semi-Markov modeling of human papillomavirus persistence |
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