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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/20864

Title: Exploring the relationship between the causal-inference and meta-analytic paradigms for the evaluation of surrogate endpoints
Authors: Van der Elst, Wim
Molenberghs, Geert
Alonso Abad, Ariel
Issue Date: 2016
Citation: STATISTICS IN MEDICINE 35(8), p. 1281-1298
Abstract: Nowadays, two main frameworks for the evaluation of surrogate endpoints, based on causal-inference and metaanalysis, dominate the scene. Earlier work showed that the metrics of surrogacy introduced in both paradigms are related, although in a complex way that is difficult to study analytically. In the present work, this relationship is further examined using simulations and the analysis of a case study. The results indicate that the extent to which both paradigms lead to similar conclusions regarding the validity of the surrogate, depends on a complex interplay between multiple factors like the ratio of the between and within trial variability and the unidentifiable correlations between the potential outcomes. All the analyses were carried out using the newly developed R package Surrogate, which is freely available via CRAN
Notes: Van der Elst, W (reprint author), Univ Hasselt, BioStat 1, Agoralaan 1, B-3590 Diepenbeek, Belgium. wim.Vanderelst@gmail.com
URI: http://hdl.handle.net/1942/20864
DOI: 10.1002/sim.6807
ISI #: 000371683600004
ISSN: 0277-6715
Category: A1
Type: Journal Contribution
Validation: ecoom, 2017
Appears in Collections: Research publications

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