![]() ![]() The research team adopted Efron’s empirical null framework for assessing statistical significance of the DACT test. The results explain why these two tests are underpowered, and more importantly motivate us to develop a more powerful Divide-Aggregate Composite-null Test (DACT) for the composite null hypothesis of no mediation effect by leveraging epigenome-wide data. Lin will show that the null distribution of Sobel’s test is not the standard normal distribution and the null distribution of the joint significant test is not uniform under the composite null of no mediation effect. Two popular tests, the Wald-type Sobel’s test and the joint significant test using the traditional null distribution are underpowered and thus can miss important scientific discoveries. However, statistical inference for causal mediation effects is challenged by the fact that one needs to test a large number of composite null hypotheses across the whole epigenome. In genome-wide epigenetic studies, it is of great scientific interest to assess whether the effect of exposure on a clinical outcome is mediated through DNA methylations. Large-Scale Hypothesis Testing for Causal Mediation Effects with Applications in Genome-wide Epigenetic Studies Greenberg Distinguished Lecture Seriesįeaturing Professor Xihong Lin, Harvard University ![]()
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