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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/404

Title: Validation of surrogate endpoints in multiple randomized clinical trials with discrete outcomes
Authors: Renard, Didier
Geys, Helena
Molenberghs, Geert
Burzykowski, Tomasz
Buyse, Marc E.
Keywords: Clinical trials
Categorical data
Surrogate Markers
Clustered data
Issue Date: 2002
Citation: Biometrical Journal, 44(8). p. 921-935
Abstract: This article extends the work of Buyse et al. (2000) on the validation of surrogate endpoints in a meta-analytic setting to the case of two discrete outcomes, the focus being on binary endpoints. The methodology entails fitting of a joint model for the surrogate and the true endpoints that includes several random effects. We propose to fit this model using a pairwise likelihood (PL) approach which seems better suited to the problem at hand than maximum likelihood or penalized quasi-likelihood. The performance of the PL estimator is evaluated on the grounds of limited simulations and the methodology is illustrated on data from a meta-analysis of five clinical trials comparing antipsychotic agents for the treatment of chronic schizophrenia
URI: http://hdl.handle.net/1942/404
DOI: 10.1002/bimj.200290004
ISI #: 000180140400001
ISSN: 0323-3847
Category: A1
Type: Journal Contribution
Validation: ecoom, 2004
Appears in Collections: Research publications

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