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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/22794

Title: Generalized Linear Mixed Models - Overview
Authors: Verbeke, Geert
Molenberghs, Geert
Issue Date: 2013
Publisher: SAGE
Citation: Scott, Marc A.; Simonoff, Jeffrey S.; Marx, Brian D. (Ed.). The SAGE Handbook of Multilevel Modeling, SAGE, p. 127-140
Abstract: In applied sciences, one is often confronted with the collection of correlated data or otherwise hierarchical data. This generic term embraces a multitude of data structures, such as multivariate observations, clustered data, repeated measurements, longitudinal data, and spatially correlated data. In particular, studies are often designed to investigate changes in a specific outcome which is measured repeatedly over time in the participating persons. This is in contrast to cross-sectional studies where the response of interest is measured only once for each individual. Longitudinal studies are conceived for the investigation of such changes, together with the evolution of relevant covariates.
URI: http://hdl.handle.net/1942/22794
Link to publication: https://www.researchgate.net/publication/292653324_Generalized_linear_mixed_models-overview
DOI: 10.4135/9781446247600.n8
ISBN: 9780857025647
Category: B2
Type: Book Section
Appears in Collections: Research publications

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