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Updated: Sep 8, 2025

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers
Published on: January 5, 2018
Residualization: justification, properties and application
Catalina B García1, Román Salmerón1, Claudia García2
1Department of Quantitative Methods for Economics and Business, University of Granada, Granada, Spain.
Abstract:
Although it is usual to find collinearity in econometric models, it is commonly disregarded. An extended solution is to eliminate the variable causing the problem but, in some cases, this decision can affect the goal of the research. Alternatively, residualization not only allows mitigation of collinearity, but it also provides an alternative interpretation of the coefficients isolating the effect of the residualized variable. This paper fully develops the residualization procedure and justifies its application not only for dealing with multicollinearity but also for separating the individual effects of the regressor variables. This contribution is illustrated by two econometric models with financial and ecological data, although it can also be extended to many different fields.
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