@misc{10481/86530,
year = {2022},
month = {12},
url = {https://hdl.handle.net/10481/86530},
abstract = {Transformation of the observed data is a very common practice when a troubling degree of near multicollinearity is detected in a linear regression model. However, it is important to take into account that these transformations may affect the detection of this problem, so they should not be performed systematically. In this paper we analyze the transformation of the data when applying the R package mcvis, showing that it only detects essential near multicollinearity when the studentise transformation is performed.},
organization = {This work has been supported by project PP2019-EI-02 of the University of Granada (Spain), by project A-SEJ-496-UGR20 of the Andalusian Government’s Counseling of Economic Transformation, Industry, Knowledge and Universities (Spain) and by project I+D+i PID2019-107767GA-I0 financed by MCIN/AEI/10.13039/501100011033.},
publisher = {The R Foundation},
keywords = {Multicolinealidad},
keywords = {R package},
keywords = {detección},
title = {Limitations in detecting multicollinearity due to scaling issues in the “mcvis” package},
doi = {https://doi.org/10.32614/RJ-2023-010},
author = {Salmerón Gómez, Román and García García, Catalina and Rodríguez Sánchez, Ainara and García García, Claudia},
}