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Full-Text Articles in Applied Statistics
Bootstrapping Confidence Intervals For Robust Measures Of Association, Jason E. King
Bootstrapping Confidence Intervals For Robust Measures Of Association, Jason E. King
Journal of Modern Applied Statistical Methods
A Monte Carlo simulation study compared four bootstrapping procedures in generating confidence intervals for the robust Winsorized and percentage bend correlations. Results revealed the superior resiliency of the robust correlations over r, with neither outperforming the other. Unexpectedly, the bootstrapping procedures achieved roughly equivalent outcomes for each correlation.