Procedures for Estimating Standardized Regression Coefficients From Sample Data

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Abstract
This paper is concerned with the role played by the standardized regression coefficients in linear regression analysis. The linear regression model is reparameterized to explicitly contain standardized regression coefficients. Several estimators of these coefficients are considered. It is shown that the usual beta coefficient is a good estimator of the coefficients in the linear regression model with random predictor variables. However, in the linear regression model with nonstochastic predictors, alternative estimators are better than the usual beta coefficient. A sociological application is included in order to display the empirical behavior of the various estimators.

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