Scholars@Duke

• Background
• 

  Education, Training, & Certifications

  • Ph.D., Johns Hopkins University 2006
  • B.S., Peking University (China) 2001
• 

  Duke Appointment History

  • Associate Professor of Statistical Science, Statistical Science, Trinity College of Arts & Sciences 2015 - 2021
  • Assistant Professor of Statistical Science, Statistical Science, Trinity College of Arts & Sciences 2008 - 2015
• Expertise
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  Subject Headings

  • Algorithms
  • Bias
  • Cluster Analysis
  • Computer Simulation
  • Health Surveys
  • Healthcare Disparities
  • Image Processing, Computer-Assisted
  • Medicare
  • Monte Carlo Method
  • Predictive Value of Tests
  • Propensity Score
  • Psychometrics
  • Retrospective Studies
  • Statistics, Nonparametric
• Research
• 

  Selected Grants

  • Innovative Biostatistical Methods for Analysis and Assessment of Clinical Trials Augmented by Real World Data awarded by Burroughs Wellcome Fund 2021 - 2026
  • New causal inference methods for cluster randomized trials with post-randomization selection awarded by Patient Centered Outcomes Research Institute 2020 - 2024
  • Addressing Bias from Missing Data in EHR Based Studies of CVD awarded by National Institutes of Health 2018 - 2023
  • The biodemography of early adversity: social behavioral processes in a wild animal model. awarded by National Institutes of Health 2018 - 2023
  • Prospective Multicenter Observational Cohort Study of Comparative Effectiveness of Disease-Modifying Treatments for Myasthenia Gravis (MG) awarded by Patient Centered Outcomes Research Institute 2017 - 2022
  • Methods for the Design and Conduct of Subgroup Analysis in Observational Studies awarded by Patient Centered Outcomes Research Institute 2019 - 2022
  • Religion, Spirituality and CVD Risks: A Focus on African Americans awarded by National Institutes of Health 2017 - 2022
  • A life course perspective on the effects of cumulative early adversity on health awarded by University of Notre Dame 2017 - 2022
  • New weighting methods for causal inference awarded by  National Science Foundation 2014 - 2017
  • NCRN-MN:Triangle Census Research Network awarded by  National Science Foundation 2011 - 2016
  • Collaborative Research: Statistical Modeling and Inference for High-dimensional Multi-Subject Neuroimaging Data awarded by  National Science Foundation 2012 - 2015
  • Bayesian multivariate analysis for causal inference with intermediate variable awarded by  National Science Foundation 2012 - 2015
• Publications & Artistic Works
• 

  Selected Publications

  • Academic Articles

    • Yang, Siyun, Fan Li, and Laine E. Thomas. “Covariate adjustment in subgroup analyses of randomized clinical trials: A propensity score approach.” Clin Trials, July 16, 2021, 17407745211028588. https://doi.org/10.1177/17407745211028588.
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    • Zeng, S., S. Rosenbaum, S. C. Alberts, E. A. Archie, and F. Li. “Causal mediation analysis for sparse and irregular longitudinal data.” Annals of Applied Statistics 15, no. 2 (June 1, 2021): 747–67. https://doi.org/10.1214/20-AOAS1427.
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    • Yang, Siyun, Elizabeth Lorenzi, Georgia Papadogeorgou, Daniel M. Wojdyla, Fan Li, and Laine E. Thomas. “Propensity score weighting for causal subgroup analysis.” Stat Med, May 12, 2021. https://doi.org/10.1002/sim.9029.
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    • Zeng, Shuxi, Fan Li, and Rui Wang. “Propensity score weighting for covariate adjustment in randomized clinical trials.” Statistics in Medicine 40, no. 4 (February 2021): 842–58. https://doi.org/10.1002/sim.8805.
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    • Li, Fan, and Laine E. Thomas. “RE:"ADDRESSING EXTREME PROPENSITY SCORES VIA THE OVERLAP WEIGHTS".” Am J Epidemiol 190, no. 1 (January 4, 2021): 189–90. https://doi.org/10.1093/aje/kwaa229.
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    • Assaad, Serge, Shuxi Zeng, Henry Pfister, Fan Li, and Lawrence Carin. “Hölder Bounds for Sensitivity Analysis in Causal Reasoning.” Corr abs/2107.04661 (2021).
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    • Li, F., A. Mercatanti, T. Mäkinen, and A. Silvestrini. “A regression discontinuity design for ordinal running variables: Evaluating central bank purchases of corporate bonds.” Annals of Applied Statistics 15, no. 1 (January 1, 2021): 304–22. https://doi.org/10.1214/20-AOAS1396.
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    • Mäkinen, Taneli, Andrea Mercatanti, Andrea Silvestrini, and Fan Li. “Effects of Eligibility for Central Bank Purchases on Corporate Bond Spreads.” Bank of Italy Temi Di Discussione (Working Paper), no. 1300 (November 11, 2020).
    • Zhang, Yi-Na, Yun Chen, Ying Wang, Fan Li, Michelle Pender, Na Wang, Fei Yan, Xiao-Hua Ying, Sheng-Lan Tang, and Chao-Wei Fu. “Reduction in healthcare services during the COVID-19 pandemic in China.” Bmj Glob Health 5, no. 11 (November 2020). https://doi.org/10.1136/bmjgh-2020-003421.
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    • Zeng, S., F. Li, and P. Ding. “Is being an only child harmful to psychological health?: evidence from an instrumental variable analysis of China's one-child policy.” Journal of the Royal Statistical Society. Series A: Statistics in Society 183, no. 4 (October 1, 2020): 1615–35. https://doi.org/10.1111/rssa.12595.
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    • Rosenbaum, Stacy, Shuxi Zeng, Fernando A. Campos, Laurence R. Gesquiere, Jeanne Altmann, Susan C. Alberts, Fan Li, and Elizabeth A. Archie. “Social bonds do not mediate the relationship between early adversity and adult glucocorticoids in wild baboons.” Proceedings of the National Academy of Sciences of the United States of America 117, no. 33 (August 3, 2020): 20052–62. https://doi.org/10.1073/pnas.2004524117.
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    • Thomas, Laine E., Fan Li, and Michael J. Pencina. “Overlap Weighting: A Propensity Score Method That Mimics Attributes of a Randomized Clinical Trial.” Jama 323, no. 23 (June 16, 2020): 2417–18. https://doi.org/10.1001/jama.2020.7819.
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    • Dong, Jing, Junni L. Zhang, Shuxi Zeng, and Fan Li. “Subgroup balancing propensity score.” Statistical Methods in Medical Research 29, no. 3 (March 2020): 659–76. https://doi.org/10.1177/0962280219870836.
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    • Thomas, Laine, Fan Li, and Michael Pencina. “Using Propensity Score Methods to Create Target Populations in Observational Clinical Research.” Jama 323, no. 5 (February 4, 2020): 466–67. https://doi.org/10.1001/jama.2019.21558.
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    • Assaad, Serge, Shuxi Zeng, Chenyang Tao, Shounak Datta, Nikhil Mehta, Ricardo Henao, Fan Li, and Lawrence Carin. “Counterfactual Representation Learning with Balancing Weights.” Corr abs/2010.12618 (2020).
    • Ding, P., and F. Li. “A Bracketing Relationship between Difference-in-Differences and Lagged-Dependent-Variable Adjustment.” Political Analysis 27, no. 4 (October 1, 2019): 605–15. https://doi.org/10.1017/pan.2019.25.
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    • Wang, F., J. Wang, A. E. Gelfand, and F. Li. “Disease Mapping With Generative Models.” American Statistician 73, no. 3 (July 3, 2019): 213–23. https://doi.org/10.1080/00031305.2017.1392358.
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    • Papadogeorgou, G., and F. Li. “Discussion of “Penalized Spline of Propensity Methods for Treatment Comparison”.” Journal of the American Statistical Association 114, no. 525 (January 2, 2019): 32–35. https://doi.org/10.1080/01621459.2018.1543120.
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    • Li, Fan, and Laine E. Thomas. “Addressing Extreme Propensity Scores via the Overlap Weights.” Am J Epidemiol 188, no. 1 (January 1, 2019): 250–57. https://doi.org/10.1093/aje/kwy201.
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    • Arnold, Suzanne V., David J. Cohen, David Dai, Philip G. Jones, Fan Li, Laine Thomas, Suzanne J. Baron, et al. “Predicting Quality of Life at 1 Year After Transcatheter Aortic Valve Replacement in a Real-World Population.” Circ Cardiovasc Qual Outcomes 11, no. 10 (October 2018): e004693. https://doi.org/10.1161/CIRCOUTCOMES.118.004693.
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    • Kaufman, Brystana G., David Klemish, Cordt T. Kassner, Jerome P. Reiter, Fan Li, Matthew Harker, Emily C. O’Brien, Donald H. Taylor, and Nrupen A. Bhavsar. “Predicting Length of Hospice Stay: An Application of Quantile Regression.” J Palliat Med 21, no. 8 (August 2018): 1131–36. https://doi.org/10.1089/jpm.2018.0039.
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    • Ding, P., and F. Li. “Causal inference: A missing data perspective.” Statistical Science 33, no. 2 (May 1, 2018): 214–37. https://doi.org/10.1214/18-STS645.
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    • Li, F., K. L. Morgan, and A. M. Zaslavsky. “Balancing Covariates via Propensity Score Weighting.” Journal of the American Statistical Association 113, no. 521 (January 2, 2018): 390–400. https://doi.org/10.1080/01621459.2016.1260466.
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    • Wang, Feifei, Jian Wang, Alan Gelfand, and Fan Li. “Accommodating the ecological fallacy in disease mapping in the absence of individual exposures.” Statistics in Medicine 36, no. 30 (December 2017): 4930–42. https://doi.org/10.1002/sim.7494.
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    • Mercatanti, A., and F. Li. “Do debit cards decrease cash demand?: causal inference and sensitivity analysis using principal stratification.” Journal of the Royal Statistical Society. Series C: Applied Statistics 66, no. 4 (August 1, 2017): 759–76. https://doi.org/10.1111/rssc.12193.
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    • Brennan, J Matthew, Laine Thomas, David J. Cohen, David Shahian, Alice Wang, Michael J. Mack, David R. Holmes, et al. “Transcatheter Versus Surgical Aortic Valve Replacement: Propensity-Matched Comparison.” J Am Coll Cardiol 70, no. 4 (July 25, 2017): 439–50. https://doi.org/10.1016/j.jacc.2017.05.060.
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    • Akande, O., F. Li, and J. Reiter. “An Empirical Comparison of Multiple Imputation Methods for Categorical Data.” American Statistician 71, no. 2 (April 3, 2017): 162–70. https://doi.org/10.1080/00031305.2016.1277158.
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    • Li, F., A. Mattei, and F. Mealli. “Evaluating the causal effect of university grants on student dropout: Evidence from a regression discontinuity design using principal stratification.” Annals of Applied Statistics 9, no. 4 (December 1, 2015): 1906–31. https://doi.org/10.1214/15-AOAS881.
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    • Zhang, Tingting, Jingwei Wu, Fan Li, Brian Caffo, and Dana Boatman-Reich. “A Dynamic Directional Model for Effective Brain Connectivity using Electrocorticographic (ECoG) Time Series.” Journal of the American Statistical Association 110, no. 509 (March 2015): 93–106. https://doi.org/10.1080/01621459.2014.988213.
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    • Li, F., T. Zhang, Q. Wang, M. Z. Gonzalez, E. L. Maresh, and J. A. Coan. “Spatial Bayesian variable selection and grouping for high-dimensional scalar-on-image regression.” Annals of Applied Statistics 9, no. 2 (January 1, 2015): 687–713. https://doi.org/10.1214/15-AOAS818.
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    • Mercatanti, A., F. Li, and F. Mealli. “Improving inference of Gaussian mixtures using auxiliary variables.” Statistical Analysis and Data Mining 8, no. 1 (January 1, 2015): 34–48. https://doi.org/10.1002/sam.11256.
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    • Schliep, E. M., T. Q. Dong, A. E. Gelfand, and F. Li. “Modeling individual tree growth by fusing diameter tape and increment core data.” Environmetrics 25, no. 8 (December 1, 2014): 610–20. https://doi.org/10.1002/env.2324.
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    • Zhang, Tingting, Fan Li, Marlen Z. Gonzalez, Erin L. Maresh, and James A. Coan. “A semi-parametric nonlinear model for event-related fMRI.” Neuroimage 97 (August 2014): 178–87. https://doi.org/10.1016/j.neuroimage.2014.04.017.
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    • Li, F., M. Baccini, F. Mealli, E. R. Zell, C. E. Frangakis, and D. B. Rubin. “Multiple Imputation by Ordered Monotone Blocks With Application to the Anthrax Vaccine Research Program.” Journal of Computational and Graphical Statistics 23, no. 3 (July 3, 2014): 877–92. https://doi.org/10.1080/10618600.2013.826583.
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    • Li, F., and F. Mealli. “A conversation with Donald B. Rubin.” Statistical Science 29, no. 3 (January 1, 2014): 439–57. https://doi.org/10.1214/14-STS489.
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    • Liu, F., S. Chakraborty, F. Li, Y. Liu, and A. C. Lozano. “Bayesian regularization via graph Laplacian.” Bayesian Analysis 9, no. 2 (January 1, 2014): 449–74. https://doi.org/10.1214/14-BA860.
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    • Mercatanti, A., and F. Li. “Do debit cards increase household spending? Evidence from a semiparametric causal analysis of a survey.” Annals of Applied Statistics 8, no. 4 (January 1, 2014): 2485–2508. https://doi.org/10.1214/14-AOAS784.
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    • Mattei, A., F. Li, and F. Mealli. “Exploiting multiple outcomes in Bayesian principal stratification analysis with application to the evaluation of a job training program.” Annals of Applied Statistics 7, no. 4 (December 1, 2013): 2336–60. https://doi.org/10.1214/13-AOAS674.
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    • Li, Fan, Alan M. Zaslavsky, and Mary Beth Landrum. “Propensity score weighting with multilevel data.” Statistics in Medicine 32, no. 19 (August 2013): 3373–87. https://doi.org/10.1002/sim.5786.
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    • Zhang, Tingting, Fan Li, Lane Beckes, and James A. Coan. “A semi-parametric model of the hemodynamic response for multi-subject fMRI data.” Neuroimage 75 (July 2013): 136–45. https://doi.org/10.1016/j.neuroimage.2013.02.048.
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    • Zhang, Tingting, Fan Li, Lane Beckes, Casey Brown, and James A. Coan. “Nonparametric inference of the hemodynamic response using multi-subject fMRI data.” Neuroimage 63, no. 3 (November 2012): 1754–65. https://doi.org/10.1016/j.neuroimage.2012.08.014.
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    • Schwartz, Scott, Fan Li, and Jerome P. Reiter. “Sensitivity analysis for unmeasured confounding in principal stratification settings with binary variables.” Statistics in Medicine 31, no. 10 (May 2012): 949–62. https://doi.org/10.1002/sim.4472.
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    • Schwartz, S. L., F. Li, and F. Mealli. “A bayesian semiparametric approach to intermediate variables in causal inference.” Journal of the American Statistical Association 106, no. 496 (December 1, 2011): 1331–44. https://doi.org/10.1198/jasa.2011.ap10425.
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    • Go, Vivian F., Constantine Frangakis, Le Van Nam, Teerada Sripaipan, Anna Bergenstrom, Fan Li, Carl Latkin, David D. Celentano, and Vu Minh Quan. “Characteristics of high-risk HIV-positive IDUs in Vietnam: implications for future interventions.” Substance Use & Misuse 46, no. 4 (January 2011): 381–89. https://doi.org/10.3109/10826084.2010.505147.
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    • Schwartz, S. L., F. Li, and J. P. Reiter. “Sensitivity analysis for unmeasured confounding in principal stratification.” Statistics in Medicine in press (2011).
    • Li, Fan, and Alan M. Zaslavsky. “Using a short screening scale for small-area estimation of mental illness prevalence for schools.” Journal of the American Statistical Association 105, no. 492 (December 2010): 1323–32. https://doi.org/10.1198/jasa.2010.ap09185.
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    • Li, F., and N. R. Zhang. “Bayesian variable selection in structured high-dimensional covariate spaces with applications in genomics.” Journal of the American Statistical Association 105, no. 491 (September 1, 2010): 1202–14. https://doi.org/10.1198/jasa.2010.tm08177.
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    • Li, Fan, Jennifer Greif Green, Ronald C. Kessler, and Alan M. Zaslavsky. “Estimating prevalence of serious emotional disturbance in schools using a brief screening scale.” International Journal of Methods in Psychiatric Research 19 Suppl 1 (June 2010): 88–98. https://doi.org/10.1002/mpr.315.
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    • Baccini, M., S. Cook, C. E. Frangakis, F. Li, F. Mealli, D. B. Rubin, and E. R. Zell. “Multiple imputation by ordered monotone blocks.” Chance 23, no. 2 (2010): 16–23.
    • Li, F., and A. M. Zaslavsky. “Using a short screening scale for small-area estimation of prevalence of serious emotional disturbance for schools.” Journal of the American Statistical Association 105, no. 492 (2010): 1323–32.
    • Li, Fan, and Constantine E. Frangakis. “Polydesigns and causal inference.” Biometrics 62, no. 2 (June 2006): 343–51. https://doi.org/10.1111/j.1541-0420.2005.00494.x.
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    • Li, Fan, and Constantine E. Frangakis. “Designs in partially controlled studies: messages from a review.” Statistical Methods in Medical Research 14, no. 4 (August 2005): 417–31. https://doi.org/10.1191/0962280205sm405oa.
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    • Li, Fan. “Propensity Score Weighting for Causal Inference with Multi-valued Treatments,” n.d.
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  • Conference Papers

    • Assaad, Serge, Shuxi Zeng, Chenyang Tao, Shounak Datta, Nikhil Mehta, Ricardo Henao, Fan Li, and Lawrence Carin. “Counterfactual Representation Learning with Balancing Weights.” In Aistats, edited by Arindam Banerjee and Kenji Fukumizu, 130:1972–80. PMLR, 2021.
    • Lu, D., C. Tao, J. Chen, F. Li, F. Guo, and L. Carin. “Reconsidering generative objectives for counterfactual reasoning.” In Advances in Neural Information Processing Systems, Vol. 2020-December, 2020.
• Teaching & Mentoring
• 

  Recent Courses

  • STA 540L: Case Studies in Statistical and Data Science 2021
  • STA 640: Causal Inference 2020
  • STA 995: Internship 2020
  • STA 440: Case Studies in the Practice of Statistics 2019
  • STA 701S: Readings in Statistical Science 2019
  • STA 723: Case Studies in Bayesian Statistics 2019

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