TY  - JOUR
AU  - Rivas, Danny Villegas 
AU  - Sánchez, José M. Palacios 
AU  - Rivero, Cristina A. Alzamora 
AU  - Del Carpio, Carlos M. Franco 
AU  - Carrera, César Osorio 
AU  - Vasquez, Martin Grados 
AU  - Calderón, Luis Ramírez 
AU  - Rojas, Karin Ponce 
AU  - Figueroa, José Jorge Rodríguez 
AU  - Narrea, Felicia L. Cáceres 
AU  - Pachas, Delia A. Saravia 
AU  - Felipe, Arrieta Benoutt 
AU  - Neyra Flores, Arturo N. 
AU  - Zata Pupuche, Pedro E. 
AU  - Falcón, Carlos Fabián 
AU  - Chipana Fernández, Yolanda Maribel Mercedes 
AU  - Rosas, Víctor Hugo Fernández 
AU  - Polo, Francisco Alejandro Espinoza 
AU  - Chunga Pingo, Gaby Esther 
AU  - Merejildo Vera, Mercy Carolina 
AU  - Cerna Muñoz, Carlos Alfredo 
AU  - Miranda Diaz, Luis Orlando 
AU  - Hernández López, Miguel Ángel 
AU  - Vejarano Campos, Martín Desiderio 
AU  - Bazán, Erick Delgado 
AU  - Campaña, Zadith Garrido 
AU  - Carranza, José Paredes 
AU  - Ventura, Leyli J. Aguilar 
AU  - Monroy Correa, Graciela M. 
AU  - Chicana Becerra, Ruth A. 
AU  - Barboza, Jhonny Richard Rodriguez 
AU  - Quipas Bellizza, Mariella M. 
AU  - Escudero Vilchez, Fernando Emilio 
AU  - Salazar Llerena, Silvia Liliana 
PY  - 2023
TI  - Comparison of Collinearity Indices for Linear Models in Agricultural Trials
JF  - OnLine Journal of Biological Sciences
VL  - 24
IS  - 2
DO  - 10.3844/ojbsci.2024.195.207
UR  - https://thescipub.com/abstract/ojbsci.2024.195.207
AB  - The 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.