Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/10984
Title: Modelling distortions in seroprevalence data using change-point fractional polynomials
Authors: HENS, Niel 
Kvitkovicova, A.
AERTS, Marc 
Hlubinka, D.
Beutels, P.
Issue Date: 2010
Publisher: SAGE PUBLICATIONS LTD
Source: STATISTICAL MODELLING, 10 (2). p. 159-175
Abstract: This paper shows how to model seroprevalence data using change-point fractional polynomials (FPs). The inclusion of a change point in the FP framework allows to detect distortions arising from common (often untestable) assumptions made in the estimation of the age-specific prevalence and force of infection from cross-sectional data. The method is motivated using seroprevalence data on the parvovirus B19 and the varicella zoster virus in Belgium.
Notes: [Hens, N.; Aerts, M.] Hasselt Univ, Interuniv Inst Biostat & Stat Bioinformat, B-3590 Diepenbeek, Belgium. [Hens, N.; Aerts, M.] Catholic Univ Louvain, B-3000 Louvain, Belgium. [Kvitkovicova, A.; Hlubinka, D.] Charles Univ Prague, Prague, Czech Republic. [Beutels, P.] Univ Antwerp, Ctr Evaluat Vaccinat, B-2020 Antwerp, Belgium. niel.hens@uhasselt.be
Keywords: change point; detecting distortions; fractional polynomial; model selection criteria; seroprevalence data;change point; detecting distortions; fractional polynomial; model selection criteria; seroprevalence data
Document URI: http://hdl.handle.net/1942/10984
ISSN: 1471-082X
e-ISSN: 1477-0342
DOI: 10.1177/1471082X0801000203
ISI #: 000278436800003
Category: A1
Type: Journal Contribution
Validations: ecoom 2011
Appears in Collections:Research publications

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