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Centering in Multiple Regression Does Not Always Reduce Multicollinearity: How to Tell When Your Estimates Will Not Benefit from Centering
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Olvera Astivia, Oscar L.; Kroc, Edward – Educational and Psychological Measurement, 2019
Within the context of moderated multiple regression, mean centering is recommended both to simplify the interpretation of the coefficients and to reduce the problem of multicollinearity. For almost 30 years, theoreticians and applied researchers have advocated for centering as an effective way to reduce the correlation between variables and thus…
Descriptors: Multiple Regression Analysis, Computation, Correlation, Statistical Distributions
Bootstrap Standard Error and Confidence Intervals for the Difference between Two Squared Multiple Correlation Coefficients
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Chan, Wai – Educational and Psychological Measurement, 2009
A typical question in multiple regression analysis is to determine if a set of predictors gives the same degree of predictor power in two different populations. Olkin and Finn (1995) proposed two asymptotic-based methods for testing the equality of two population squared multiple correlations, [rho][superscript 2][subscript 1] and…
Descriptors: Multiple Regression Analysis, Intervals, Correlation, Computation