Statistical Modelling 10 (2010), 159175
Modelling distortions in seroprevalence data using change-point
fractional polynomials
Niel Hens
Interuniversity Institute for Biostatistics and Statistical Bioinformatics
Hasselt University
Campus Diepenbeek, Agoralaan-Gebouw D
B3590 Diepenbeek
Belgium
and
Catholic University of Leuven
Belgium
eMail: niel.hens@uhasselt.be
A Kvitkovicova
Charles University
Prague
Czech Republic
M Aerts
Interuniversity Institute for Biostatistics and Statistical Bioinformatics
Hasselt University
and
Catholic University of Leuven
Belgium
D Hlubinka
Charles University
Prague
Czech Republic
P Beutels
Center for the Evaluation of Vaccination
Antwerp University
Antwerp
Belgium
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.
Keywords:
change point; detecting distortions; fractional polynomial;
model selection criteria; seroprevalence data
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