| SEISMIC: A self-exciting point process model for predicting tweet popularity Q Zhao, MA Erdogdu, HY He, A Rajaraman, J Leskovec Proceedings of the 21th ACM SIGKDD international conference on knowledge …, 2015 | 701 | 2015 |
| Statistical inference in two-sample summary-data Mendelian randomization using robust adjusted profile score Q Zhao, J Wang, G Hemani, J Bowden, DS Small Annals of Statistics 48 (3), 1742-1769, 2020 | 483 | 2020 |
| Causal interpretations of black-box models Q Zhao, T Hastie Journal of Business & Economic Statistics 39 (1), 272-281, 2021 | 376 | 2021 |
| Entropy balancing is doubly robust Q Zhao, D Percival Journal of Causal Inference 5 (1), 2017 | 290 | 2017 |
| Mendelian randomization E Sanderson, MM Glymour, MV Holmes, H Kang, J Morrison, MR Munafò, ... Nature Reviews Methods Primers 2 (1), 6, 2022 | 272 | 2022 |
| Improving the accuracy of two-sample summary data Mendelian randomization: moving beyond the NOME assumption J Bowden, M Fabiola Del Greco, C Minelli, D Lawlor, Q Zhao, N Sheehan, ... International Journal of Epidemiology, 159442, 2018 | 253 | 2018 |
| Covariate balancing propensity score by tailored loss functions Q Zhao Annals of Statistics 47 (2), 965-993, 2019 | 125 | 2019 |
| Confounder adjustment in multiple hypothesis testing J Wang, Q Zhao, T Hastie, AB Owen Annals of Statistics 45 (5), 1863-1894, 2017 | 117 | 2017 |
| Powerful three-sample genome-wide design and robust statistical inference in summary-data Mendelian randomization Q Zhao, C Yang, J Wang, DS Small International Journal of Epidemiology 48 (5), 1478-1492, 2019 | 111 | 2019 |
| Sensitivity analysis for inverse probability weighting estimators via the percentile bootstrap Q Zhao, DS Small, BB Bhattacharya Journal of the Royal Statistical Society (Series B, Statistical Methodology …, 2019 | 106 | 2019 |
| Selective inference for effect modification via the lasso Q Zhao, DS Small, A Ertefaie Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2021 | 63 | 2021 |
| Quantifying and addressing the prevalence and bias of study designs in the environmental and social sciences AP Christie, D Abecasis, M Adjeroud, JC Alonso, T Amano, A Anton, ... Nature communications 11 (1), 6377, 2020 | 53 | 2020 |
| Two-sample instrumental variable analyses using heterogeneous samples Q Zhao, J Wang, W Spiller, J Bowden, DS Small Statistical Science 34 (2), 317-333, 2019 | 43 | 2019 |
| On sensitivity value of pair-matched observational studies Q Zhao Journal of the American Statistical Association 114 (526), 713-722, 2019 | 39 | 2019 |
| Causal inference for heritable phenotypic risk factors using heterogeneous genetic instruments J Wang, Q Zhao, J Bowden, G Hemani, G Davey Smith, DS Small, ... PLoS genetics 17 (6), e1009575, 2021 | 36 | 2021 |
| Cross-screening in observational studies that test many hypotheses Q Zhao, DS Small, PR Rosenbaum Journal of the American Statistical Association 113 (523), 1070-1084, 2018 | 29 | 2018 |
| A Mendelian randomization study of the role of lipoprotein subfractions in coronary artery disease Q Zhao, J Wang, Z Miao, NR Zhang, S Hennessy, DS Small, DJ Rader Elife 10, e58361, 2021 | 26* | 2021 |
| BETS: The dangers of selection bias in early analyses of the coronavirus disease (COVID-19) pandemic Q Zhao, N Ju, S Bacallado, R Shah Annals of Applied Statistics 15 (1), 363-390, 2020 | 26 | 2020 |
| Analysis of the epidemic growth of the early 2019-nCoV outbreak using internationally confirmed cases Q Zhao, Y Chen, DS Small MedRxiv, 2020.02. 06.20020941, 2020 | 24 | 2020 |
| Toward better practice of covariate adjustment in analyzing randomized clinical trials T Ye, J Shao, Y Yi, Q Zhao Journal of the American Statistical Association, 1-13, 2022 | 23 | 2022 |
Dylan SmallProfessor of Statistics, University of PennsylvaniaVerified email at wharton.upenn.edu
