MultiColl package and other packages to detect multicollinearity in R

TL;DR

This paper introduces the multiColl package in R for detecting multicollinearity, highlighting its unique ability to handle qualitative variables and intercepts, and compares its performance with other packages.

Contribution

The paper presents the multiColl package as a novel tool in R that effectively addresses multicollinearity, especially with qualitative variables and intercepts, which is not well-covered by existing packages.

Findings

multiColl effectively detects multicollinearity in models with qualitative variables

multiColl provides advantages over existing R packages in multicollinearity detection

Comparison shows multiColl's results are consistent and beneficial for regression analysis

Abstract

This work presents a guide for the use of some of the functions of the multiColl package in R for the detection of near-multicollinearity. The main contribution, in comparison to other existing packages in R or other econometric software, is the treatment of qualitative independent variables and the intercept in the simple/multiple linear regression model. The main goal of this paper is to show the advantages of the multiColl package in R, comparing its results with the results obtained by other existing packages in R for the treatment of multicollinearity.