258 citations · 299 across the 4 of their papers we have counts for
4 papers
Powerful genome-wide design and robust statistical inference in two-sample summary-data Mendelian randomization
Qingyuan Zhao, Yang Chen, Jingshu Wang +1
Two-sample summary-data Mendelian randomization (MR) has become a popular research design to estimate the causal effect of risk exposures. With the sample size of GWAS continuing t…
Statistical inference in two-sample summary-data Mendelian randomization using robust adjusted profile score
Qingyuan Zhao, Jingshu Wang, Gibran Hemani +2
Mendelian randomization (MR) is a method of exploiting genetic variation to unbiasedly estimate a causal effect in presence of unmeasured confounding. MR is being widely used in ep…
Two-sample instrumental variable analyses using heterogeneous samples
Qingyuan Zhao, Jingshu Wang, Jack Bowden +1
Instrumental variable analysis is a widely used method to estimate causal effects in the presence of unmeasured confounding. When the instruments, exposure and outcome are not meas…
Confounder Adjustment in Multiple Hypothesis Testing
Jingshu Wang, Qingyuan Zhao, Trevor Hastie +1
We consider large-scale studies in which thousands of significance tests are performed simultaneously. In some of these studies, the multiple testing procedure can be severely bias…