SUBSETBYVIF: Stata module to select a subset of covariates constrained by VIF

Walton Plummer () and William D. Dupont ()
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William D. Dupont: Vanderbilt University School of Medicine

Statistical Software Components from Boston College Department of Economics

Abstract: subsetByVIF selects subsets of the covariates listed in varlist such that each covariate in a given subset has a VIF that is less than or equal to a specified value given by viflist. We are frequently faced with analyzing data sets in which the ratio of covariates to patients is high. There are several approaches to analyzing such data including penalized regression methods, k-fold cross-validation techniques, and bagging. A problem with any of these approaches is that, even after the elimination of variables causing multi-collinearity, the variance-covariance matrix of the remaining covariates is often highly ill-conditioned. The subsetByVIF program reduces the number of covariates to the largest subsample such that the maximum VIF for each variable in the subsample is less than some value specified by the user. These variables are selected without regard to the dependent variable of interest, which should mitigate problems due to overfitting. The use of this program should improve the convergence properties of many methods of exploratory data analysis.

Language: Stata
Requires: Stata version 15
Keywords: covariates; VIF; subset; conditioning (search for similar items in EconPapers)
Date: 2019-04-21, Revised 2019-04-28
Note: This module should be installed from within Stata by typing "ssc install subsetbyvif". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
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Downloads: (external link)
http://fmwww.bc.edu/repec/bocode/s/subsetbyvif.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/s/subsetbyvif.sthlp help file (text/plain)
http://fmwww.bc.edu/repec/bocode/s/sample_subsetbyvif.do sample do file (text/plain)

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