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FARMS: a new algorithm for variable selection

Author
Perez, S.; Gómez Melis, Guadalupe; Brander, C.
Type of activity
Journal article
Journal
Biomed Research International
Date of publication
2015-01-01
Volume
2015
Number
ID 319797
First page
1
Last page
11
DOI
https://doi.org/10.1155/2015/319797 Open in new window
Project funding
Grup de Recerca en Bioestadística i Bioinformàtica (GRBIO)
Métodos avanzados en estudios de seguimiento: diseño de ensayos clínicos, datos longitudinales y censura en un intervalo
Repository
http://hdl.handle.net/2117/86075 Open in new window
URL
http://www.hindawi.com/journals/bmri/2015/319797/ Open in new window
Abstract
Large datasets including an extensive number of covariates are generated these days in many different situations, for instance, in detailed genetic studies of outbreed human populations or in complex analyses of immune responses to different infections. Aiming at informing clinical interventions or vaccine design, methods for variable selection identifying those variables with the optimal prediction performance for a specific outcome are crucial. However, testing for all potential subsets of var...
Citation
Pérez, S., Gomez, G., Brander, C. FARMS: a new algorithm for variable selection. "Biomed Research International", 01 Gener 2015, vol. 2015, núm. ID 319797, p. 1-11.
Keywords
genome, immune, markers, models, performance, regression, t-cell responses
Group of research
GRBIO - Biostatistics and Bioinformatics Research Group

Participants

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