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- W2059408902 abstract "Multicollinearity is a serious problem in regression analysis. High correlation among predictor variables can lead to unstable estimates of the regression coefficients. Principal components offers one approach to reducing the sampling variance of the coefficient estimates. However, this method produces biased estimates and the bias cannot be measured without knowledge of the true coefficients. This paper uses simulation to study the degree of bias in a model employing real economic data." @default.
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- W2059408902 title "Using simulation to measure bias in principal components regression" @default.
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