@article{TQMP22-2-78,
    author =    {Susam, Selim Orhun AND Hudaverdi, Burcu },
    journal =   {The Quantitative Methods for Psychology},
    publisher = {TQMP},
    title =     {A Copula-Based Piecewise Health Concentration Curve for Modeling Stress-Related Performance Inequalities},
    year =      {2026},
    volume =    {22},
    number =    {2},
    url =       {http://www.tqmp.org/RegularArticles/vol22-2/p078/p078.pdf },
    pages =     {78-89},
    abstract =  {Health concentration curves are essential tools for quantifying inequalities in health outcomes across socioeconomic or biological gradients. In this study, we propose a novel copula-based piecewise health concentration curve constructed with the gluing copula technique and use it to reveal important insights into how stress-related biomarkers relate to inequalities in concentration performance. We employ stress-related concentration performance data for modeling localized changes in the dependence structure between concentration performance and stress-related variables, including cortisol, alpha-amylase responses, state anxiety, and cognitive stress appraisal. Through the application of this technique to experimental data from stress and unstress groups, we demonstrate how health concentration curves diverge from the line of equality and highlight stress-related biomarker ranges where concentration differences in performance are most noticeable. Our results show significant variations in concentration inequalities across stress biomarkers, emphasizing the significance of taking nonlinear dependence into account when evaluating how stress affects cognitive function. This copula-based approach offers an effective instrument for measuring and comparing health disparities in situations where the ability to focus under pressure is crucial, providing information for focused interventions aimed at minimizing performance gaps.},
    doi =       {10.20982/tqmp.22.2.p078}
}