5 papers
Disentangled Feature Importance
Jin-Hong Du, Kathryn Roeder, Larry Wasserman
When predictors are statistically dependent, the appropriate definition of feature importance depends on the operational goal. Conditional-incremental measures are well-suited for…
Active multiple testing with proxy p-values and e-values
Ziyu Xu, Catherine Wang, Larry Wasserman +2
Researchers often lack the resources to test every hypothesis of interest directly or compute test statistics comprehensively, but often possess auxiliary data from which we can co…
Assumption-Lean Post-Integrated Inference with Surrogate Control Outcomes
Jin-Hong Du, Kathryn Roeder, Larry Wasserman
Data integration methods aim to extract low-dimensional embeddings from high-dimensional outcomes to remove unwanted variations, such as batch effects and unmeasured covariates, ac…
Causal Inference for Genomic Data with Multiple Heterogeneous Outcomes
Jin-Hong Du, Zhenghao Zeng, Edward H. Kennedy +2
With the evolution of single-cell RNA sequencing techniques into a standard approach in genomics, it has become possible to conduct cohort-level causal inferences based on single-c…
Simultaneous inference for generalized linear models with unmeasured confounders
Jin-Hong Du, Larry Wasserman, Kathryn Roeder
Tens of thousands of simultaneous hypothesis tests are routinely performed in genomic studies to identify differentially expressed genes. However, due to unmeasured confounders, ma…