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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/14440

Title: Joint modeling of hierarchically clustered and overdispersed non-gaussian continuous outcomes for comet assay data
Authors: Ghebretinsae, Aklilu Habteab
Faes, Christel
Molenberghs, Geert
Geys, Helena
Van der Leede, Bas-Jan
Issue Date: 2012
Citation: PHARMACEUTICAL STATISTICS, 11 (6), p. 449-455
Abstract: Multivariate longitudinal or clustered data are commonly encountered in clinical trials and toxicological studies. Typically, there is no single standard endpoint to assess the toxicity or efficacy of the compound of interest, but co-primary endpoints are available to assess the toxic effects or the working of the compound. Modeling the responses jointly is thus appealing to draw overall inferences using all responses and to capture the association among the responses. Non-Gaussian outcomes are often modeled univariately using exponential family models. To accommodate both the overdispersion and hierarchical structure in the data, Molenberghs et al. A family of generalized linear models for repeated measures with normal and conjugate random effects. Statistical Science 2010; 25:325347 proposed using two separate sets of random effects. This papers considers a model for multivariate data with hierarchically clustered and overdispersed non-Gaussian data. Gamma random effect for the over-dispersion and normal random effects for the clustering in the data are being used. The two outcomes are jointly analyzed by assuming that the normal random effects for both endpoints are correlated. The association structure between the response is analytically derived. The fit of the joint model to data from a so-called comet assay are compared with the univariate analysis of the two outcomes.
Notes: [Ghebretinsae, Aklilu Habteab; Faes, Christel; Molenberghs, Geert; Geys, Helena] Univ Hasselt, I BioStat, B-3590 Diepenbeek, Belgium. [Molenberghs, Geert] Katholieke Univ Leuven, I BioStat, B-3000 Louvain, Belgium. [Geys, Helena; Van der Leede, Bas-Jan] Janssen Pharmaceut, B-2430 Beerse, Belgium.
URI: http://hdl.handle.net/1942/14440
DOI: 10.1002/pst.1533
ISI #: 000310789600003
ISSN: 1539-1604
Category: A1
Type: Journal Contribution
Validation: ecoom, 2013
Appears in Collections: Research publications

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