{
  "creator": [
    "Li, Johnson Ching-Hong",
    "Tze, Virginia Man Chung"
  ],
  "date": [
    "2021-03-31"
  ],
  "description": [
    "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 measuring the relationship between age and sexual compulsivity."
  ],
  "format": [
    "application/pdf",
    "text/html",
    "text/xml"
  ],
  "identifier": [
    "https://meth.psychopen.eu/index.php/meth/article/view/4495",
    "10.5964/meth.4495"
  ],
  "language": [
    "eng"
  ],
  "publisher": [
    "PsychOpen GOLD / Leibniz Institut for Psychology (ZPID)"
  ],
  "relation": [
    "https://meth.psychopen.eu/index.php/meth/article/view/4495/4495.pdf",
    "https://meth.psychopen.eu/index.php/meth/article/view/4495/4495.html",
    "https://meth.psychopen.eu/index.php/meth/article/view/4495/4495.xml"
  ],
  "rights": [
    "Copyright (c) 2021 Johnson Ching-Hong Li, Virginia Man Chung Tze",
    "https://creativecommons.org/licenses/by/4.0"
  ],
  "source": [
    "Methodology; Vol. 17 No. 1 (2021); 1-21",
    "1614-2241",
    "1614-1881",
    "10.5964/meth.v17i1"
  ],
  "subject": [
    "common-language effect size",
    "confidence intervals",
    "bootstrapping",
    "Monte Carlo simulation",
    "probability-of-superiority"
  ],
  "title": [
    "Analytic and Bootstrap Confidence Intervals for the Common-Language Effect Size Estimate"
  ],
  "type": [
    "info:eu-repo/semantics/article",
    "info:eu-repo/semantics/publishedVersion",
    "Peer-reviewed article"
  ]
}