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A Guide to Using the R Package “multiColl” for Detecting Multicollinearity

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Abstract

The detection of problematic collinearity in a linear regression model is treated in all the existing statistical software packages. However, such detection is not always done adequately. The main shortcomings relate to treatment of independent qualitative variables and completely ignoring the role of the intercept in the model (consequently, ignoring the nonessential collinearity). This paper presents the R package multiColl, which implements the usually applied measures for detecting near collinearity while overcoming the weaknesses observed in other existing packages.

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Notes

  1. This value differs from the threshold equal to 0.7 provided by Halkos and Tsilika (2018) to indicate a problem of near collinearity.

  2. García et al. (2018) show that values of the determinant of the correlation matrix lower than \(0.1013 + 0.00008626 \cdot n - 0.01384 \cdot k\) indicate the presence of problematic near essential multicollinearity. Once again, this value differs from the threshold provided by Field (2019), who claims that when the value of the determinant of the correlation matrix is less than 0.00001 there is severe multicollinearity. In the example presented by Halkos and Tsilika (2018), the conclusion is that collinearity is not detected since the value of the determinant of the matrix of correlations (0.00663839) is higher than the threshold (0.00001). However, taking into account the paper presented by García et al. (2018), the threshold will be 0.01964016 and, consequently, severe near collinearity is detected.

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Authors and Affiliations

  1. Department of Quantitative Methods for the Economy and Business, University of Granada, Granada, Spain

    Román Salmerón-Gómez & Catalina García-García

  2. Department of Economics and Business, University of Almería, Almería, Spain

    José García-Pérez

Authors
  1. Román Salmerón-Gómez
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  2. Catalina García-García
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  3. José García-Pérez
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Correspondence to Catalina García-García.

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Salmerón-Gómez, R., García-García, C. & García-Pérez, J. A Guide to Using the R Package “multiColl” for Detecting Multicollinearity. Comput Econ 57, 529–536 (2021). https://doi.org/10.1007/s10614-019-09967-y

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