A powerful test for ordinal trait genetic association analysis
Ding Juan and
Li Qizhai ()
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Zhang Sanguo: School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing, China
Wang Jinjuan: LSC, NCMIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China
Ding Juan: School of Mathematics and Statistics, Guangxi Normal University, Guilin, China
Li Qizhai: LSC, NCMIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Zhongguancun East Road, 55, Beijing 100190, China, Phone: +86-10-82541839
Statistical Applications in Genetics and Molecular Biology, 2019, vol. 18, issue 2, 9
Response selective sampling design is commonly adopted in genetic epidemiologic study because it can substantially reduce time cost and increase power of identifying deleterious genetic variants predispose to human complex disease comparing with prospective design. The proportional odds model (POM) can be used to fit data obtained by this design. Unlike the logistic regression model, the estimated genetic effect based on POM by taking data as being enrolled prospectively is inconsistent. So the power of resulted Wald test is not satisfactory. The modified POM is suitable to fit this type of data, however, the corresponding Wald test is not optimal when the genetic effect is small. Here, we propose a new association test to handle this issue. Simulation studies show that the proposed test can control the type I error rate correctly and is more powerful than two existing methods. Finally, we applied three tests to Anticyclic Citrullinated Protein Antibody data from Genetic Workshop 16.
Keywords: ordinal response; power; proportional odds model; response selective sampling (search for similar items in EconPapers)
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