Bootstrap Confidence Intervals for 11 Robust Correlations in the Presence of Outliers and Leverage Observations

Abstract: Researchers often examine whether two continuous variables (X and Y) are linearly related. Pearson’s correlation (r) is a widely-employed statistic for assessing bivariate linearity. However, the accuracy of r is known to decrease when data contain outliers and/or leverage observations, a circumstance common in behavioral and social sciences research. This study compares 11 robust correlations with r and evaluates the associated bootstrap confidence intervals [bootstrap standard interval (BSI), bootstrap percentile interval (BPI), and bootstrap bias-corrected-and-accelerated interval (BCaI)] across conditions with and without outliers and/or leverage observations. The simulation results showed that the median-absolute-deviation correlation (r-MAD), median-based correlation (r-MED), and trimmed correlation (r-TRIM) consistently outperformed the other estimates, including r, when data contain outliers and/or leverage observations. This study provides an easy-to-use R code for computi.... https://meth.psychopen.eu/index.php/meth/article/view/8467

Object Details

• Location: Deutsche Nationalbibliothek Frankfurt am Main
• Extent: Online-Ressource
• Language: Englisch

References and Relationships

• Bibliographic citation: Bootstrap Confidence Intervals for 11 Robust Correlations in the Presence of Outliers and Leverage Observations ; volume:18 ; number:2 ; day:30 ; month:06 ; year:2022 ; Methodology ; 18, Heft 2 (30.06.2022)

Contributors, Places and Time

• Creator: Li, Johnson Ching-Hong

Further information

• DOI: 10.5964/meth.8467
• URN: urn:nbn:de:101:1-2022080605091389527202
• Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Last update: 15.08.2025, 7:32 AM CEST