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http://hdl.handle.net/1942/1465
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DC Field | Value | Language |
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dc.contributor.author | SHKEDY, Ziv | - |
dc.contributor.author | AERTS, Marc | - |
dc.contributor.author | MOLENBERGHS, Geert | - |
dc.contributor.author | Beutels, Phillipe | - |
dc.contributor.author | Van Damme, Pierre | - |
dc.date.accessioned | 2007-05-07T08:39:59Z | - |
dc.date.available | 2007-05-07T08:39:59Z | - |
dc.date.issued | 2006 | - |
dc.identifier.citation | STATISTICS IN MEDICINE, 25(9). p. 1577-1591 | - |
dc.identifier.issn | 0277-6715 | - |
dc.identifier.uri | http://hdl.handle.net/1942/1465 | - |
dc.description.abstract | The force of infection is one of the primary epidemiological parameters of infectious diseases. For many infectious diseases it is assumed that the force of infection is age-dependent. Although the force of infection can be estimated directly from a follow up study, it is much more common to have cross-sectional seroprevalence data from which the prevalence and the force of infection can be estimated. In this paper, we propose to model the force of infection within the framework of fractional polynomials. We discuss several parametric examples from the literature and show that all of these examples can be expressed as special cases of fractional polynomial models. We illustrate the method on five seroprevalence samples, two of Hepatitis A, and one of Rubella, Mumps and Varicella. | - |
dc.description.sponsorship | We thank the associate editor and the referee for their valuable comments, which improved the pre-sentation of the paper substantially. The first three authors gratefully acknowledge the financial supportfrom the IAP research network No. P5=24 of the Belgian Government (Belgian Science Policy). | - |
dc.language.iso | en | - |
dc.rights | (C) 2005 John Wiley & Sons, Ltd. | - |
dc.subject.other | seroprevalence; force of infection; conventional polynomials; fractional polynomials; generalized linear models; REGRESSION; RUBELLA; MEASLES; MUMPS | - |
dc.subject.other | seroprevalence; force of infection; conventional polynomials; fractional polynomials;generalized linear models | - |
dc.title | Modelling age-dependent force of infection from prevalence data using fractional polynomials | - |
dc.type | Journal Contribution | - |
dc.identifier.epage | 1591 | - |
dc.identifier.issue | 9 | - |
dc.identifier.spage | 1577 | - |
dc.identifier.volume | 25 | - |
local.bibliographicCitation.jcat | A1 | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
dc.bibliographicCitation.oldjcat | A1 | - |
dc.identifier.doi | 10.1002/sim.2291 | - |
dc.identifier.isi | 000237366000010 | - |
item.validation | ecoom 2007 | - |
item.accessRights | Restricted Access | - |
item.fullcitation | SHKEDY, Ziv; AERTS, Marc; MOLENBERGHS, Geert; Beutels, Phillipe & Van Damme, Pierre (2006) Modelling age-dependent force of infection from prevalence data using fractional polynomials. In: STATISTICS IN MEDICINE, 25(9). p. 1577-1591. | - |
item.fulltext | With Fulltext | - |
item.contributor | SHKEDY, Ziv | - |
item.contributor | AERTS, Marc | - |
item.contributor | MOLENBERGHS, Geert | - |
item.contributor | Beutels, Phillipe | - |
item.contributor | Van Damme, Pierre | - |
crisitem.journal.issn | 0277-6715 | - |
crisitem.journal.eissn | 1097-0258 | - |
Appears in Collections: | Research publications |
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Shkedy_et_al-2006-Statistics_in_Medicine.pdf Restricted Access | Published version | 312 kB | Adobe PDF | View/Open Request a copy |
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