Bootstrapping Confidence Intervals For Robust Measures Of Association

  title={Bootstrapping Confidence Intervals For Robust Measures Of Association},
  author={Jason E. King},
A Monte Carlo simulation study was conducted to determine the bootstrap correction formula yielding the most accurate confidence intervals for robust measures of association. Confidence intervals were generated via the percentile, adjusted, BC, and BC(a) bootstrap procedures and applied to the Winsorized, percentage bend, and Pearson correlation coefficients. Type I error, bias, efficiency, and interval length were compared across correlational and bootstrap methods. Results reveal the superior… CONTINUE READING

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