Analytic and Bootstrap Confidence Intervals for the Common-Language Effect Size Estimate

Abstract: Evaluating how an effect-size estimate performs between two continuous variables based on the common-language effect size (CLES) has received increasing attention. While Blomqvist (1950; https://doi.org/10.1214/aoms/1177729754) developed a parametric estimator (q') for the CLES, there has been limited progress in further refining CLES. This study: a) extends Blomqvist’s work by providing a mathematical foundation for Bp (a non-parametric version of CLES) and an analytic approach for estimating its standard error; and b) evaluates the performance of the analytic and bootstrap confidence intervals (CIs) for Bp. The simulation shows that the bootstrap bias-corrected-and-accelerated interval (BCaI) has the best protected Type 1 error rate with a slight compromise in Power, whereas the analytic-t CI has the highest overall Power but with a Type 1 error slightly larger than the nominal value. This study also uses a real-world data-set to demonstrate the applicability of the CLES in measu.... https://meth.psychopen.eu/index.php/meth/article/view/4495

Object Details

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

References and Relationships

• Bibliographic citation: Analytic and Bootstrap Confidence Intervals for the Common-Language Effect Size Estimate ; volume:17 ; number:1 ; day:31 ; month:03 ; year:2021 ; Methodology ; 17, Heft 1 (31.03.2021)

Contributors, Places and Time

• Creator: Li, Johnson Ching-Hong ; Tze, Virginia Man Chung

Further information

• DOI: 10.5964/meth.4495
• URN: urn:nbn:de:101:1-2021050105091385441612
• Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Last update: 14.08.2025, 10:46 AM CEST