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http://hdl.handle.net/1942/42351
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DC Field | Value | Language |
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dc.contributor.author | ALONSO ABAD, Ariel | - |
dc.contributor.author | ONG, Fenny | - |
dc.contributor.author | Stijven, Florian | - |
dc.contributor.author | VAN DER ELST, Wim | - |
dc.contributor.author | MOLENBERGHS, Geert | - |
dc.contributor.author | VAN KEILEGOM, Ingrid | - |
dc.contributor.author | VERBEKE, Geert | - |
dc.contributor.author | Callegaro, Andrea | - |
dc.date.accessioned | 2024-02-08T15:19:51Z | - |
dc.date.available | 2024-02-08T15:19:51Z | - |
dc.date.issued | 2024 | - |
dc.date.submitted | 2024-01-29T14:05:01Z | - |
dc.identifier.citation | STATISTICS IN MEDICINE, | - |
dc.identifier.uri | http://hdl.handle.net/1942/42351 | - |
dc.description.abstract | Within the causal association paradigm, a method is proposed to assess the validity of a continuous outcome as a surrogate for a binary true endpoint. The methodology is based on a previously introduced information-theoretic definition of surrogacy and has two main steps. In the first step, a new model is proposed to describe the joint distribution of the potential outcomes associated with the putative surrogate and the true endpoint of interest. The identifiability issues inherent to this type of models are handled via sensitivity analysis. In the second step, a metric of surrogacy new to this setting, the so-called individual causal association is presented. The methodology is studied in detail using theoretical considerations, some simulations, and data from a randomized clinical trial evaluating an inactivated quadrivalent influenza vaccine. A user-friendly R package Surrogate is provided to carry out the evaluation exercise. | - |
dc.language.iso | en | - |
dc.publisher | Wiley | - |
dc.subject.other | causal inference | - |
dc.subject.other | correlates protection | - |
dc.subject.other | information theory | - |
dc.subject.other | surrogate endpoints | - |
dc.title | An information‐theoretic approach for the assessment of a continuous outcome as a surrogate for a binary true endpoint based on causal inference: Application to vaccine evaluation | - |
dc.type | Journal Contribution | - |
local.bibliographicCitation.jcat | A1 | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
local.bibliographicCitation.status | Early view | - |
local.type.programme | VSC | - |
dc.identifier.doi | 10.1002/sim.9997 | - |
dc.identifier.isi | WOS:001134072000001 | - |
local.provider.type | - | |
local.uhasselt.international | no | - |
item.fulltext | With Fulltext | - |
item.accessRights | Embargoed Access | - |
item.contributor | ALONSO ABAD, Ariel | - |
item.contributor | ONG, Fenny | - |
item.contributor | Stijven, Florian | - |
item.contributor | VAN DER ELST, Wim | - |
item.contributor | MOLENBERGHS, Geert | - |
item.contributor | VAN KEILEGOM, Ingrid | - |
item.contributor | VERBEKE, Geert | - |
item.contributor | Callegaro, Andrea | - |
item.fullcitation | ALONSO ABAD, Ariel; ONG, Fenny; Stijven, Florian; VAN DER ELST, Wim; MOLENBERGHS, Geert; VAN KEILEGOM, Ingrid; VERBEKE, Geert & Callegaro, Andrea (2024) An information‐theoretic approach for the assessment of a continuous outcome as a surrogate for a binary true endpoint based on causal inference: Application to vaccine evaluation. In: STATISTICS IN MEDICINE,. | - |
item.embargoEndDate | 2024-07-01 | - |
crisitem.journal.issn | 0277-6715 | - |
crisitem.journal.eissn | 1097-0258 | - |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
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2024, Alonso A, An information-theoretic approach BinCont.pdf Restricted Access | Early view | 2.59 MB | Adobe PDF | View/Open Request a copy |
SIM-22-0851.R3_Proof_hi.pdf Until 2024-07-01 | Peer-reviewed author version | 1.08 MB | Adobe PDF | View/Open Request a copy |
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