Using Double-Lasso Regression for Principled Variable Selection

70 Pages Posted: 18 Feb 2016

See all articles by Oleg Urminsky

Oleg Urminsky

University of Chicago - Booth School of Business

Christian Hansen

University of Chicago - Booth School of Business - Econometrics and Statistics

Victor Chernozhukov

Massachusetts Institute of Technology (MIT) - Department of Economics; New Economic School

Date Written: 2016

Abstract

The decision of whether to control for covariates, and how to select which covariates to include, is ubiquitous in psychological research. Failing to control for valid covariates can yield biased parameter estimates in correlational analyses or in imperfectly randomized experiments and contributes to underpowered analyses even in effectively randomized experiments. We introduce double-lasso regression as a principle method for variable selection. The double lasso method is calibrated to not over-select potentially spurious covariates, and simulations demonstrate that using this method reduces error and increases statistical power. This method can be used to identify which covariates have sufficient empirical support for inclusion in analyses of correlations, moderation, mediation and experimental interventions, as well as to test for the effectiveness of randomization. We illustrate both the method’s usefulness and how to implement it in practice by applying it to four analyses from the prior literature, using both correlational and experimental data.

Keywords: research methods, covariate, regression, variable selection, confound, omitted variable bias

Suggested Citation

Urminsky, Oleg and Hansen, Christian and Chernozhukov, Victor, Using Double-Lasso Regression for Principled Variable Selection (2016). Available at SSRN: https://ssrn.com/abstract=2733374 or http://dx.doi.org/10.2139/ssrn.2733374

Oleg Urminsky (Contact Author)

University of Chicago - Booth School of Business ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States

Christian Hansen

University of Chicago - Booth School of Business - Econometrics and Statistics ( email )

Chicago, IL 60637
United States
773-834-1702 (Phone)

Victor Chernozhukov

Massachusetts Institute of Technology (MIT) - Department of Economics ( email )

50 Memorial Drive
Room E52-262f
Cambridge, MA 02142
United States
617-253-4767 (Phone)
617-253-1330 (Fax)

HOME PAGE: http://www.mit.edu/~vchern/

New Economic School

100A Novaya Street
Moscow, Skolkovo 143026
Russia

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