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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/665

Title: Design-based analysis of surveys: a bovine herpesvirus 1 case study
Authors: Speybroeck, N.
Boelaert, Frank
Renard, Didier
Burzykowski, Tomasz
Mintiens, Koen
Molenberghs, Geert
Berkvens, Dirk
Keywords: Statistical methodology
Issue Date: 2003
Citation: Epidemiology and Infection, 131(2). p. 991-1002
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.
URI: http://hdl.handle.net/1942/665
Link to publication: http://dspace.itg.be/bitstream/handle/10390/639/2003einf0991.pdf?sequence=1
DOI: 10.1017/S095026880300102X
ISI #: 000186339100023
ISSN: 0950-2688
Category: A1
Type: Journal Contribution
Validation: ecoom, 2004
Appears in Collections: Research publications

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