Comparison of collinearity indices for linear models in agricultural trials

dc.contributor.authorRivas Villegas, Danny
dc.contributor.authorRivero Alzamora, Cristina
dc.contributor.authorCarrera Osorio, César
dc.contributor.authorCalderón Ramírez, Luis
dc.contributor.authorRojas Correa, Liliana
dc.contributor.authorNarrea Cáceres
dc.contributor.authorSánchez Palacios, José
dc.contributor.authorDel Carpio Franco, Carlos
dc.contributor.authorVásquez Grados, Martín
dc.contributor.authorSalinas Cruz, Luis
dc.contributor.authorRojas Ponce, Karin
dc.contributor.authorFigu
dc.date.accessioned2024-02-29T20:50:25Z
dc.date.available2024-02-29T20:50:25Z
dc.date.issued2024
dc.descriptionIndexado en Scopus.
dc.descriptionEl texto completo de este trabajo no está disponible en el Repositorio Institucional UNIFE. Deberá acceder por el DOI ó URL de la casa editorial externa.
dc.descriptionOnLine Journal of Biological Sciences; Vol. 24, 2-2024; pp. 195-207
dc.description.abstractThe deleterious consequences of collinearity in linear regression on the precision of estimators of regression coefficients and the interpretability of the fitted model are widely recognized. In this study, we compare several methodologies for assessing collinearity in linear models and explore the effect of outliers on collinearity. The robustness of collinearity measures (individual and overall) is validated through two detailed Monte Carlo simulation study which also considers the effect of outliers on collinearity indices. The methods are illustrated with two real-world agricultural and fish morphology l data sets to show potential applications. The results do not provide any evidence for an effect from outliers on collinearity identification using the collinearity indices (individual and overall). The FG and Fj collinearity indices more robust as both sample size and collinearity degree increase. The VIF (individual measure) had a better performance on the fitted model with a greater number of parameters. © 2024, Science Publications. All rights reserved.es_PE
dc.identifier.doihttps://doi.org/10.3844/ojbsci.2024.195.207
dc.identifier.journalOnline Journal of Biological Sciences
dc.identifier.urihttp://hdl.handle.net/20.500.11955/1210
dc.identifier.urlhttps://www.scopus.com/record/display.uri?eid=2-s2.0-85182479071&doi=10.3844%2fojbsci.2024.195.207&origin=inward&txGid=fc0a374fb3eee26a0ed23da0e4cd1639
dc.language.isoeng
dc.publisherScience Publications
dc.publisher.countryAE
dc.relation.ispartofurn:issn:16084217
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourceRepositorio Institucional – UNIFÉ
dc.subjectColinealidad
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#4.01.01
dc.titleComparison of collinearity indices for linear models in agricultural trials
dc.typeinfo:eu-repo/semantics/article
unife.autor.afiliacionQuipas Bellizza, Mariella Margot

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