Contributions to Quantile Equivalence Testing

Diplôme Thèse Contributions to Quantile Equivalence Testing eng 2026-04-15 2026-04-15 director Guerrier Stéphane 625357 Services communs du département des sciences de la terre (DETCO) author Wu Jun 0009-0003-2853-4303 977012 10.13097/archive-ouverte/unige:194060 urn:nbn:ch:unige-1940605 GSEM 165 This thesis mainly investigates statistical methods for quantile-based equivalence testing, with applications in clinical trials and pharmaceutical development. In many settings, treatment effects cannot be adequately characterized by mean comparisons alone, making equivalence assessment at specific quantiles a valuable alternative for evaluating efficacy and safety. The thesis considers equivalence testing for a single quantile in two independent Gaussian populations with unequal variances. Existing methods based on the Two One-Sided Tests procedure for quantiles (qTOST) are often conservative in finite samples, resulting in reduced statistical power. To address this issue, a finite-sample adjustment procedure is proposed. Theoretical results and simulation studies show that the proposed method maintains the nominal significance level while achieving uniformly higher power than qTOST. The proposed method extends the framework to simultaneous equivalence testing of multiple quantiles. Novel size-matched procedures are developed to overcome the conservativeness of conventional approaches. The proposed methods provide accurate type I error control while substantially improving power and reducing sample size requirements, particularly in unbalanced and heteroscedastic settings. Computational tools and reproducible software are developed to support practical implementation. Simulation studies and pharmaceutical applications demonstrate the effectiveness and applicability of the proposed methods. Dewey 310 117 Research Center for Statistics S5 false 0c4f5974-4423-49b3-859e-0c9b8132205a Thesis Restricted Jun_Wu_PhD_thesis_Quantile_Equivale.pdf 5297770 application/pdf Private 2028-06-12 590ff51e8347fa214669010ef367541119e8a98dda533b77c90ba864ff22f36e 421a179f-bca4-41b1-86d1-2b704e820eaa Imprimatur Public Imprimatur_WU_Jun_15.04.2026.pdf 122140 application/pdf 53fa352e6270108c0343b420e58f6f13682890350ff2f6601c9be129692fc5a1 embargoedAccess Faculté d'économie et de management / Research Center for Statistics

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Wu, Jun

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