Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/4032
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dc.contributor.authorTILAHUN ESHETE, Abel-
dc.contributor.authorPryseley, Assam-
dc.contributor.authorALONSO ABAD, Ariel-
dc.contributor.authorMOLENBERGHS, Geert-
dc.date.accessioned2007-12-07T14:50:31Z-
dc.date.available2007-12-07T14:50:31Z-
dc.date.issued2007-
dc.identifier.citationCOMPUTATIONAL STATISTICS & DATA ANALYSIS, 51(9). p. 4152-4163-
dc.identifier.issn0167-9473-
dc.identifier.urihttp://hdl.handle.net/1942/4032-
dc.description.abstractThe evaluation of surrogate endpoints is thought to be first studied by Prentice, who presented a definition of a surrogate as well as a set of criteria. These criteria were later supplemented with the so-called proportion explained after notifying some drawbacks in Prentice's approach. Subsequently, the evaluation exercise was framed within a meta-analytic setting, thereby overcoming difficulties that necessarily surround evaluation efforts based on a single trial. The meta-analytic approach for continuous outcomes is briefly reviewed. Advantages and problems are highlighted by means of two case studies, one in schizophrenia and one in ophthalmology, and a simulation study. One of the critical issues for the broad adoption of methodology like the one presented here is the availability of flexible implementations in standard statistical software. Generically applicable SAS macros and R functions are developed and made available to the reader. (c) 2007 Elsevier B.V. All rights reserved.-
dc.description.sponsorshipWe gratefully acknowledge support from Belgian IUAP/PAI network “Statistical Techniques and Modeling for Complex Substantive Questions with Complex Data”.-
dc.language.isoen-
dc.publisherELSEVIER SCIENCE BV-
dc.rights© 2007 Elsevier B.V. All rights reserved-
dc.subject.otheradjusted association; hierarchical model; meta-analysis; proportion explained; random-effects model; relative effect; surrogate endpoint-
dc.subject.otheradjusted association; hierarchical model; meta-analysis; proportion explained; random-effects model; relative effect; surrogate endpoint-
dc.titleFlexible surrogate marker evaluation from several randomized clinical trials with continuous endpoints, using R and SAS-
dc.typeJournal Contribution-
dc.identifier.epage4163-
dc.identifier.issue9-
dc.identifier.spage4152-
dc.identifier.volume51-
local.format.pages12-
local.bibliographicCitation.jcatA1-
dc.description.notesHasselt Univ, Ctr Stat, B-3590 Diepenbeek, Belgium.MOLENBERGHS, G, Hasselt Univ, Ctr Stat, Agoralaan 1, B-3590 Diepenbeek, Belgium.geert.molenberghs@uhasselt.be-
local.type.refereedRefereed-
local.type.specifiedArticle-
dc.bibliographicCitation.oldjcatA1-
local.bibliographicCitation.artnrR07008-
dc.identifier.doi10.1016/j.csda.2007.02.007-
dc.identifier.isi000246606000005-
item.fullcitationTILAHUN ESHETE, Abel; Pryseley, Assam; ALONSO ABAD, Ariel & MOLENBERGHS, Geert (2007) Flexible surrogate marker evaluation from several randomized clinical trials with continuous endpoints, using R and SAS. In: COMPUTATIONAL STATISTICS & DATA ANALYSIS, 51(9). p. 4152-4163.-
item.contributorTILAHUN ESHETE, Abel-
item.contributorPryseley, Assam-
item.contributorALONSO ABAD, Ariel-
item.contributorMOLENBERGHS, Geert-
item.validationecoom 2008-
item.accessRightsRestricted Access-
item.fulltextWith Fulltext-
crisitem.journal.issn0167-9473-
crisitem.journal.eissn1872-7352-
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