University Lecturer in Statistics.
Research Interest: Causal Inference, Methodology for Large-Scale Problems, Applications in Genetics, Epidemiology, and Social Sciences.
Publications
Comment: Will Competition-Winning Methods for Causal Inference Also Succeed in Practice?
– Statistical Science
(2019)
34,
72
(doi: 10.1214/18-STS680)
Permutation $p$-value approximation via generalized Stolarsky invariance
– The Annals of Statistics
(2019)
47,
583
(doi: 10.1214/18-aos1702)
Covariate balancing propensity score by tailored loss functions
– The Annals of Statistics
(2019)
47,
965
(doi: 10.1214/18-aos1698)
Improving the accuracy of two-sample summary-data Mendelian randomization: moving beyond the NOME assumption.
– Int J Epidemiol
(2018)
48,
728
(doi: 10.1093/ije/dyy258)
Multiple Testing When Many p-Values are Uniformly Conservative, with Application to Testing Qualitative Interaction in Educational Interventions
– Journal of the American Statistical Association
(2018)
114,
1291
Defining Multimorbidity in Older Surgical Patients.
– Medical Care
(2018)
56,
701
(doi: 10.1097/MLR.0000000000000947)
On Sensitivity Value of Pair-Matched Observational Studies
– Journal of the American Statistical Association
(2018)
114,
713
Cross-Screening in Observational Studies That Test Many Hypotheses
– Journal of the American Statistical Association
(2018)
113,
1070
Graphical Diagnosis of Confounding Bias in Instrumental Variable Analysis
– Epidemiology (Cambridge, Mass.)
(2018)
29,
E29
(doi: 10.1097/EDE.0000000000000822)
Powerful genome-wide design and robust statistical inference in
two-sample summary-data Mendelian randomization
(2018)
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