490 citations · 974 across the 26 of their papers we have counts for
26 papers
Towards Efficient Inference under Nonmonotone Missingness with General Imputation
Qi Xu, Lorenzo Testa, Jing Lei +1
Missing data are ubiquitous in classical survey and longitudinal studies as well as modern multi-modality data analysis. A longstanding challenge arises under nonmonotone missingne…
Rescuing double robustness: safe estimation under complete misspecification
Lorenzo Testa, Francesca Chiaromonte, Kathryn Roeder
Double robustness is a major selling point of semiparametric and missing data methodology. Its virtues lie in protection against partial nuisance misspecification and asymptotic se…
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…
Semiparametric semi-supervised learning for general targets under distribution shift and decaying overlap
Lorenzo Testa, Qi Xu, Jing Lei +1
In modern scientific applications, large volumes of covariate data are readily available, while outcome labels are costly, sparse, and often subject to distribution shift. This asy…
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…
Augmented Doubly Robust Post-Imputation Inference for Proteomic Data
Haeun Moon, Jin-Hong Du, Jing Lei +1
Quantitative measurements produced by mass spectrometry proteomics experiments offer a direct way to explore the role of proteins in molecular mechanisms. However, analysis of such…