Statistical Modelling 10 (2010), 159–175

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
B–3590 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

Downloads:

Figures as encapsulated postscript files in zipped archive

Example data and R-code in zipped archive
back