Epidemiology and Infection



Design-based analysis of surveys: a bovine herpesvirus 1 case study


N. SPEYBROECK a1c1, F. BOELAERT a2, D. RENARD a3, T. BURZYKOWSKI a3, K. MINTIENS a2, G. MOLENBERGHS a3 and D. L. BERKVENS a1
a1 Institute for Tropical Medicine, Nationalestraat 155, 2000 Antwerp, Belgium
a2 Co-ordination Centre for Veterinary Diagnostics, Veterinary and Agrochemical Research Centre, Groeselenberg 99, 1180 Brussels, Belgium
a3 Center for Statistics, Limburgs Universitair Centrum, Universitaire Campus, 3590 Diepenbeek, Belgium

Article author query
speybroeck n   [PubMed][Google Scholar] 
boelaert f   [PubMed][Google Scholar] 
renard d   [PubMed][Google Scholar] 
burzykowski t   [PubMed][Google Scholar] 
mintiens k   [PubMed][Google Scholar] 
molenberghs g   [PubMed][Google Scholar] 
berkvens d   [PubMed][Google Scholar] 

Abstract

This paper critically assesses the design implications for the analysis of surveys of infections. It indicates the danger of not accounting for the study design in the statistical investigation of risk factors. A stratified design often implies an increased precision while clustering of infection results in a decreased precision. Through pseudo-likelihood estimation and linearisation of the variance estimator, the design effects can be taken into account in the analysis. The intra-cluster-correlation can be investigated through a logistic random effect model and a generalised estimating equation (GEE), allowing the investigation of the extent of spread of infections in a herd (cluster). The advantage of using adaptive Gaussian quadrature in a logistic random effect model is discussed. Applicable software is briefly reviewed. The methods are illustrated with data from a bovine herpesvirus 1 (BHV-1) serosurvey of Belgian cattle.

(Accepted October 6 2002)


Correspondence:
c1 Author for correspondence.


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