Generalized fiducial methods for testing quantitative trait locus effects in genetic backcross studies. Issue 2 (27th May 2022)

• Record Type: Journal Article
• Authors: Ren, Pengcheng; Liu, Guanfu; Pu, Xiaolong; Li, Yan
• Is Part Of: Statistical theory and related fields. Volume 6:Issue 2(2022)
• Page Start: 148
• Page End: 160
• Publication Date: 2022-05-27
• Subjects: Generalized fiducial inference -- quantitative trait locus -- mixture model -- Gibbs algorithm -- likelihood ratio test; Statistics -- Periodicals; Statistics; Periodicals; Electronic journals; 001.422
• DOI: 10.1080/24754269.2021.1984636
• Languages: English
• ISSNs: 2475-4269

Abstract

Abstract : In this paper, we propose generalized fiducial methods and construct four generalized p -values to test the existence of quantitative trait locus effects under phenotype distributions from a location-scale family. Compared with the likelihood ratio test based on simulation studies, our methods perform better at controlling type I errors while retaining comparable power in cases with small or moderate sample sizes. The four generalized fiducial methods support varied scenarios: two of them are more aggressive and powerful, whereas the other two appear more conservative and robust. A real data example involving mouse blood pressure is used to illustrate our proposed methods.