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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 | Source: | 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 | Keywords: | clustering; missing data; weighted generalized estimating equations | Document URI: | http://hdl.handle.net/1942/7805 | ISSN: | 1085-7117 | e-ISSN: | 1537-2693 | DOI: | 10.1198/108571107X250535 | ISI #: | 000250990100005 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2008 |
Appears in Collections: | Research publications |
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