How to Standardize Regression Coefficients

1994/08/01 by Johan Bring · 1 voice · 459 citations
Economics, Econometrics and Finance · Mathematics · #Advanced Statistical Methods and Models #Computer science #Cross-sectional regression #Data mining #Econometrics #Financial Risk and Volatility Modeling #Linear regression #Mathematics #Measure (data warehouse) #Polynomial regression #Regression #Regression analysis #Regression diagnostic #Regression dilution #Standardized coefficient #Statistical Methods and Inference #Statistics

paper · doi:10.1080/00031305.1994.10476059

published in The American Statistician 48(3), 209-213 (Taylor & Francis)

openalex publication_date 1994/08/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06

Abstract

In many regression studies, there is an ambition to compare the relative importance of different variables. One measure frequently used is standardized regression coefficients. The present article reveals an inconsistency in the definition of the standardized coefficients and demonstrates that if they were correctly defined, a comparison between standardized coefficients would be similar to comparing t values.

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Discussions

• I like this paper: not only does it review of all the reasons standardized coefficients are bad, actually, It also then goes on to show how test statistics can be used as measures of unique contribut [bsky, 92 points, 9 comments]

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