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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/9221

Title: Generalizability in non-Gaussian longitudinal clinical trial data based on generalized linear mixed models
Authors: Vangeneugden, Tony
Molenberghs, Geert
Laenen, Annouschka
Alonso Abad, Ariel
Geys, Helena
Issue Date: 2007
Publisher: TAYLOR & FRANCIS LTD
Citation: JOURNAL OF BIOPHARMACEUTICAL STATISTICS, 18(4). p. 691-712
Abstract: This work investigates how generalizability, an extension of reliability, can be defined and estimated based on longitudinal data sequences resulting from, for example, clinical studies. Useful and intuitive approximate expressions are derived based on generalized linear mixed models. Data from four double-blind, randomized clinical trials into schizophrenia motivate the research and are used to estimate generalizability for a binary response parameter.
URI: http://hdl.handle.net/1942/9221
DOI: 10.1080/10543400802071386
ISI #: 000257438900010
ISSN: 1054-3406
Category: A1
Type: Journal Contribution
Validation: ecoom, 2009
Appears in Collections: Research publications

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