Reader Reaction: A note on testing and estimation in markerâ€ set association study using semiparametric quantile regression kernel machine
Xiang Zhan and
Michael C. Wu
Biometrics, 2018, vol. 74, issue 2, 764-766
Kong et al. (2016, Biometrics 72, 364â€“371) presented a quantile regression kernel machine (QRKM) test for robust analysis of genetic markerâ€ set association studies. A potential limitation of QRKM is the permutationâ€ based test design may be unscalable for the massive sizes of modern datasets. In this article, we present an alternative strategy for pâ€ value calculation of QRKM, which is capable of speeding up the QRKM testing procedure dramatically while maintaining the same testing performance as QRKM. The effectiveness of our approach is demonstrated via simulation studies.
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