| Balancing covariates via propensity score weighting F Li, KL Morgan, AM Zaslavsky Journal of the American Statistical Association 113 (521), 390-400, 2018 | 1002 | 2018 |
| Addressing extreme propensity scores via the overlap weights F Li, LE Thomas, F Li American journal of epidemiology 188 (1), 250-257, 2019 | 623 | 2019 |
| Overlap weighting: a propensity score method that mimics attributes of a randomized clinical trial L Thomas, F Li, M Pencina Journal of American Medical Association 323 (23), 2417-2418, 2020 | 489 | 2020 |
| Propensity score weighting with multilevel data F Li, AM Zaslavsky, MB Landrum Statistics in medicine 32 (19), 3373-3387, 2013 | 323 | 2013 |
| Bayesian variable selection in structured high-dimensional covariate spaces with applications in genomics F Li, NR Zhang Journal of the American statistical association 105 (491), 1202-1214, 2010 | 250 | 2010 |
| Propensity score weighting for causal inference with multiple treatments F Li, F Li Annals of Applied Statistics 13 (4), 2389-2415., 2019 | 184 | 2019 |
| Causal Inference: A missing data perspective P Ding, F Li Statistical Science 33 (2), 214-237, 2018 | 166 | 2018 |
| Using Propensity Score Methods to Create Target Populations in Observational Clinical Research L Thomas, F Li, M Pencina JAMA 323 (5), 466-467, 2020 | 164 | 2020 |
| Reduction in healthcare services during the COVID-19 pandemic in China YN Zhang, Y Chen, Y Wang, F Li, M Pender, N Wang, F Yan, XH Ying, ... BMJ global health 5 (11), e003421, 2020 | 114 | 2020 |
| Transcatheter Versus Surgical Aortic Valve Replacement: Propensity-Matched Comparison Journal of the American College of Cardiology 70 (4), 439-450, 2017 | 99 | 2017 |
| An empirical comparison of multiple imputation methods for categorical data O Akande, F Li, J Reiter The American Statistician 71 (2), 162-170, 2017 | 99 | 2017 |
| A bracketing relationship between difference-in-differences and lagged-dependent-variable adjustment P Ding, F Li Political Analysis 27 (4), 605-615, 2019 | 96 | 2019 |
| Spatial Bayesian variable selection and grouping for high-dimensional scalar-on-image regression F Li, T Zhang, Q Wang, MZ Gonzalez, EL Maresh, JA Coan Annals of Applied Statistics 9 (2), 687-713, 2015 | 90 | 2015 |
| A Bayesian semiparametric approach to intermediate variables in causal inference SL Schwartz, F Li, F Mealli Journal of the American Statistical Association 106 (496), 1331-1344, 2011 | 90 | 2011 |
| Counterfactual representation learning with balancing weights S Assaad, S Zeng, C Tao, S Datta, N Mehta, R Henao, F Li, L Carin International Conference on Artificial Intelligence and Statistics, 1972-1980, 2021 | 80 | 2021 |
| Bayesian causal inference: a critical review F Li, P Ding, F Mealli Philosophical Transactions of the Royal Society A 381 (2247), 20220153, 2023 | 73 | 2023 |
| Evaluating the causal effect of university grants on student dropout: evidence from a regression discontinuity design using principal stratification F Li, A Mattei, F Mealli Annals of Applied Statistics 9 (4), 1906-1931, 2015 | 67* | 2015 |
| Propensity Score Weighting for Covariate Adjustment in Randomized Clinical Trials S Zeng, F Li, R Wang, F Li Statistics in Medicine 40 (4), 842-858, 2021 | 64 | 2021 |
| Do debit cards increase household spending? Evidence from a semiparametric causal analysis of a survey A Mercatanti, F Li Annals of Applied Statistics 8 (4), 2485-2508, 2014 | 61 | 2014 |
| PSweight: An R package for propensity score weighting analysis T Zhou, G Tong, F Li, LE Thomas arXiv preprint arXiv:2010.08893, 2020 | 60 | 2020 |
Laine E. ThomasDukeVerified email at duke.edu