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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/9919

Title: The correlated and shared gamma frailty model for bivariate current status data: An illustration for cross-sectional serological data
Authors: Hens, Niel
Wienke, A.
Aerts, Marc
Molenberghs, Geert
Issue Date: 2009
Citation: STATISTICS IN MEDICINE, 28(22). p. 2785-2800
Abstract: Frailty models are often used to study the individual heterogeneity in multivariate survival analysis. Whereas the shared frailty model is widely applied, the correlated frailty model has gained attention because it elevates the restriction Of unobserved factors to act similar within clusters. Estimating frailty models is not straightforward due to various types of censoring. In this paper, we Study the behavior of the bivariate-correlated gamma frailty model for type I interval-censored data, better known as Current status data. We show that applying a shared rather than a correlated frailty model to cross-sectionally collected serological data on hepatitis A and B leads to biased estimates for the baseline hazard and variance parameters. Copyright (c) 2009 John Wiley & Sons, Ltd.
Notes: [Hens, N.; Aerts, M.; Molenberghs, G.] Hasselt Univ, Interuniv Inst Biostat & Stat Bioinformat, B-3590 Diepenbeek, Limburg, Belgium. [Hens, N.] Univ Antwerp, Vaccine & Infect Dis Inst, WHO Collaborating Ctr, Ctr Evaluat Vaccinat,Ctr Hlth Econ Res & Modeling, B-2020 Antwerp, Belgium. [Wienke, A.] Univ Halle Wittenberg, Inst Med Epidemiol Biostat & Informat, Halle, Germany. [Molenberghs, G.] Catholic Univ Louvain, Interuniv Inst Biostat & Stat Bioinformat, B-3000 Louvain, Belgium.
URI: http://hdl.handle.net/1942/9919
DOI: 10.1002/sim.3660
ISI #: 000270183400004
ISSN: 0277-6715
Category: A1
Type: Journal Contribution
Validation: ecoom, 2010
Appears in Collections: Research publications

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