Please use this identifier to cite or link to this item: doi:10.22028/D291-36993
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Title: Using joint models to disentangle intervention effect types and baseline confounding: an application within an intervention study in prodromal Alzheimer's disease with Fortasyn Connect
Author(s): van Oudenhoven, Floor M
Swinkels, Sophie H. N.
Hartmann, Tobias
Soininen, Hilkka
van Hees, Anneke M. J.
Rizopoulos, Dimitris
Language: English
Title: BMC medical research methodology
Volume: 19
Issue: 1
Publisher/Platform: BioMed Central
Year of Publication: 2019
Free key words: Joint model
Intervention effect
Baseline imbalance
Fortasyn
Alzheimer’s disease
DDC notations: 610 Medicine and health
Publikation type: Journal Article
Abstract: Many prodromal Alzheimer's disease trials collect two types of data: the time until clinical diagnosis of dementia and longitudinal patient information. These data are often analysed separately, although they are strongly associated. By combining the longitudinal and survival data into a single statistical model, joint models can account for the dependencies between the two types of data.
DOI of the first publication: 10.1186/s12874-019-0791-z
URL of the first publication: https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-019-0791-z
Link to this record: urn:nbn:de:bsz:291--ds-369938
hdl:20.500.11880/33576
http://dx.doi.org/10.22028/D291-36993
ISSN: 1471-2288
Date of registration: 4-Aug-2022
Faculty: M - Medizinische Fakultät
Department: M - Neurologie und Psychiatrie
Professorship: M - Prof. Dr. Tobias Hartmann
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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