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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/7805

Title: Handling missingness when modeling the force of infection from clustered seroprevalence data
Authors: HENS, Niel
FAES, Christel
AERTS, Marc
SHKEDY, Ziv
Mintiens, Koen
LAEVENS, Hans
BOELAERT, Frank
Issue Date: 2007
Publisher: AMER STATISTICAL ASSOC & INT BIOMETRIC SOC
Citation: JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS, 12(4). p. 498-513
Abstract: Modeling infectious diseases data is a relatively young research area in which clustering and stratification are key features. It is not unlikely for these data to have missing values. If values are missing completely at random, the analysis on the complete cases is valid. However, in practice this assumption is usually not fulfilled. This article shows the effect of ignoring missing data in modeling the force of infection of the bovine herpesvirus-1 in Belgian cattle and proposes the use of weighted generalized estimating equations with constrained fractional polynomials as a flexible modeling tool.
Notes: Hasselt Univ, Ctr Stat, Diepenbeek, Belgium. Vet & Agrochem Res Ctr, Head Sect, Brussels, Belgium. Univ Ghent, Fac Med Vet, Ghent, Belgium. European Food Safety Author, Parma, Italy.Hens, N, Hasselt Univ, Ctr Stat, Diepenbeek, Belgium.niel.hens@uhasselt.be
URI: http://hdl.handle.net/1942/7805
DOI: 10.1198/108571107X250535
ISI #: 000250990100005
ISSN: 1085-7117
Category: A1
Type: Journal Contribution
Validation: ecoom, 2008
Appears in Collections: Research publications

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