| Balancing covariates via propensity score weighting F Li, KL Morgan, AM Zaslavsky Journal of the American Statistical Association 113 (521), 390-400, 2018 | 290 | 2018 |
| Propensity score weighting with multilevel data F Li, AM Zaslavsky, MB Landrum Statistics in medicine 32 (19), 3373-3387, 2013 | 193* | 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 | 186 | 2010 |
| Addressing extreme propensity scores via the overlap weights F Li, LE Thomas, F Li American journal of epidemiology 188 (1), 250-257, 2019 | 89 | 2019 |
| Transcatheter Versus Surgical Aortic Valve Replacement: Propensity-Matched Comparison Journal of the American College of Cardiology 70 (4), 439-450, 2017 | 61 | 2017 |
| 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 | 54 | 2011 |
| Causal inference: A missing data perspective P Ding, F Li Statistical Science 33 (2), 214-237, 2018 | 43 | 2018 |
| An empirical comparison of multiple imputation methods for categorical data O Akande, F Li, J Reiter The American Statistician 71 (2), 162-170, 2017 | 42 | 2017 |
| 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 The Annals of Applied Statistics 9 (2), 687-713, 2015 | 41 | 2015 |
| Do debit cards increase household spending? Evidence from a semiparametric causal analysis of a survey A Mercatanti, F Li The Annals of Applied Statistics 8 (4), 2485-2508, 2014 | 38 | 2014 |
| 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 | 34* | 2015 |
| Using Propensity Score Methods to Create Target Populations in Observational Clinical Research L Thomas, F Li, M Pencina JAMA 323 (5), 466-467, 2020 | 33 | 2020 |
| Sensitivity analysis for unmeasured confounding in principal stratification settings with binary variables S Schwartz, F Li, JP Reiter Statistics in medicine 31 (10), 949-962, 2012 | 31 | 2012 |
| Propensity score weighting for causal inference with multiple treatments F Li, F Li Annals of Applied Statistics 13 (4), 2389-2415., 2019 | 29 | 2019 |
| A dynamic directional model for effective brain connectivity using electrocorticographic (ECoG) time series T Zhang, J Wu, F Li, B Caffo, D Boatman-Reich Journal of the American Statistical Association 110 (509), 93-106, 2015 | 29 | 2015 |
| Bayesian regularization via graph Laplacian F Liu, S Chakraborty, F Li, Y Liu, AC Lozano Bayesian Analysis 9 (2), 449-474, 2014 | 29* | 2014 |
| A semi-parametric model of the hemodynamic response for multi-subject fMRI data T Zhang, F Li, L Beckes, JA Coan NeuroImage 75, 136-145, 2013 | 29 | 2013 |
| Exploiting multiple outcomes in Bayesian principal stratification analysis with application to the evaluation of a job training program A Mattei, F Li, F Mealli Annals of Applied Statistics 7 (4), 2336-2360, 2013 | 29* | 2013 |
| Multiple imputation by ordered monotone blocks with application to the anthrax vaccine research program F Li, M Baccini, F Mealli, ER Zell, CE Frangakis, DB Rubin Journal of Computational and Graphical Statistics 23 (3), 877-892, 2014 | 28 | 2014 |
| Imputing missing data by fully conditional models: Some cautionary examples and guidelines F Li, Y Yu, DB Rubin Duke University Department of Statistical Science Discussion Paper 11 (14), 1-35, 2012 | 28 | 2012 |
Fabrizia MealliUniversity of FlorenceEmail verificata su ds.unifi.it
