Title
Handling missingness when modeling the force of infection from clustered seroprevalence data Handling missingness when modeling the force of infection from clustered seroprevalence data
Author
Faculty/Department
Faculty of Medicine and Health Sciences
Publication type
article
Publication
Alexandria, Va ,
Subject
Mathematics
Human medicine
Source (journal)
Journal of agricultural, biological, and environmental statistics / American Statistical Association; International Biometric Society. - Alexandria, Va
Volume/pages
12(2007) :4 , p. 498-513
ISSN
1085-7117
ISI
000250990100005
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
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.
E-info
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