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  "Title": "Composite Kernel Machine Regression Based on Likelihood Ratio\nTest",
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  "Author": "Ni Zhao [aut], Haoyu Zhang [aut, cre]",
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  "Description": "Composite Kernel Machine Regression based on Likelihood\nRatio Test (CKLRT): in this package, we develop a kernel\nmachine regression framework to model the overall genetic\neffect of a SNP-set, considering the possible GE interaction.\nSpecifically, we use a composite kernel to specify the overall\ngenetic effect via a nonparametric function and we model\nadditional covariates parametrically within the regression\nframework. The composite kernel is constructed as a weighted\naverage of two kernels, one corresponding to the genetic main\neffect and one corresponding to the GE interaction effect. We\npropose a likelihood ratio test (LRT) and a restricted\nlikelihood ratio test (RLRT) for statistical significance. We\nderive a Monte Carlo approach for the finite sample\ndistributions of LRT and RLRT statistics. (N. Zhao, H. Zhang,\nJ. Clark, A. Maity, M. Wu. Composite Kernel Machine Regression\nbased on Likelihood Ratio Test with Application for Combined\nGenetic and Gene-environment Interaction Effect (Submitted).)",
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