Eric Laber
Professor of Statistical Science
My work is focused on the use of statistical reinforcement learning to inform decision making in complex and dynamic environments.
Current Appointments & Affiliations
- Professor of Statistical Science, Statistical Science, Trinity College of Arts & Sciences 2021
- Professor of Biostatistics & Bioinformatics, Biostatistics & Bioinformatics, Basic Science Departments 2021
- Research Professor of Global Health, Duke Global Health Institute, University Institutes and Centers 2021
Contact Information
- 221 Old Chem Bldg, Durham, NC 27708
- Box 90251, Durham, NC 27708-0251
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eric.laber@duke.edu
(919) 684-4210
- Background
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Education, Training, & Certifications
- Ph.D., University of Michigan, Ann Arbor 2011
- M.A., University of Michigan, Ann Arbor 2007
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Previous Appointments & Affiliations
- Scholar In Residence of Statistical Science, Statistical Science, Trinity College of Arts & Sciences 2020
- Recognition
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In the News
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MAY 4, 2023 Duke Today -
FEB 22, 2021 Duke Research Blog -
SEP 30, 2020
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- Research
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Selected Grants
- A randomized controlled trial of a novel, evidence-based algorithm for managing lower respiratory tract infection in a resource-limited setting awarded by National Institutes of Health 2022 - 2027
- Integrated Biostatistical Training for CVD Research awarded by North Carolina State University 2022 - 2027
- Using a SMART Design to Optimize PTSD Symptom Management Strategies Among Cancer Survivors awarded by National Institutes of Health 2019 - 2024
- FACT: Near Real-Time Spatiotemporal Resource Allocation to Improve Swine Health awarded by North Carolina State University 2021 - 2024
- FlexED: A Digital, Gamified Early Intervention for Eating Disorders based on Acceptance and Commitment Therapy awarded by National Institutes of Health 2022 - 2024
- A Patient-centered Intervention Using Technology to Reduce Colorectal Cancer Disparities in Primary Care awarded by University of Florida 2021 - 2024
- A randomized controlled trial of iACT, a novel mHealth intervention for eating disorders in type 1 diabetes awarded by Juvenile Diabetes Research Foundation 2022 - 2023
- CAREER: Big Computation and the Management of Emerging Infectious Diseases awarded by National Science Foundation 2021 - 2022
- RAPID: Planning for the present and future management of COVID-19 awarded by National Science Foundation 2021 - 2022
- A Pragmatic Trial of an Adaptive eHealth HIV Prevention Program for Diverse Adolescent MSM awarded by Northwestern University 2021 - 2022
- Building a reinforcement learning tool for individually tailoring just-in-time adaptive interventions: Extending the reach of mHealth technology for improved weight loss outcomes awarded by University of North Carolina - Chapel Hill 2021 - 2022
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External Relationships
- Amazon
- Chapman Hall/CRC Press
- Publications & Artistic Works
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Selected Publications
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Academic Articles
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Dai, Kathy Z., Eric B. Laber, Huaxuan Chen, Robert J. Mentz, and Chetna Malhotra. “Hand Grip Strength Predicts Mortality and Quality of Life in Heart Failure: Insights From the Singapore Cohort of Patients With Advanced Heart Failure.” J Card Fail, December 13, 2022. https://doi.org/10.1016/j.cardfail.2022.11.009.Full Text Link to Item
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Weltz, Justin, Alex Volfovsky, and Eric B. Laber. “Reinforcement Learning Methods in Public Health.” Clinical Therapeutics 44, no. 1 (January 2022): 139–54. https://doi.org/10.1016/j.clinthera.2021.11.002.Full Text
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Rose, Eric J., Eric B. Laber, Marie Davidian, Anastasios A. Tsiatis, Ying-Qi Zhao, and Michael R. Kosorok. “Sample Size Calculations for SMARTs,” June 16, 2019.Link to Item
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Luckett, Daniel J., Eric B. Laber, Samer S. El-Kamary, Cheng Fan, Ravi Jhaveri, Charles M. Perou, Fatma M. Shebl, and Michael R. Kosorok. “Receiver Operating Characteristic Curves and Confidence Bands for Support Vector Machines,” July 17, 2018.Link to Item
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Laber, Eric B., Fan Wu, Catherine Munera, Ilya Lipkovich, Salvatore Colucci, and Steve Ripa. “Identifying optimal dosage regimes under safety constraints: An application to long term opioid treatment of chronic pain.” Statistics in Medicine 37, no. 9 (April 2018): 1407–18. https://doi.org/10.1002/sim.7566.Full Text
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Kelleher, Sarah A., Caroline S. Dorfman, Jen C. Plumb Vilardaga, Catherine Majestic, Joseph Winger, Vicky Gandhi, Christine Nunez, et al. “Optimizing delivery of a behavioral pain intervention in cancer patients using a sequential multiple assignment randomized trial SMART.” Contemp Clin Trials 57 (June 2017): 51–57. https://doi.org/10.1016/j.cct.2017.04.001.Full Text Link to Item
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Zhang, Yichi, Eric B. Laber, Anastasios Tsiatis, and Marie Davidian. “Using decision lists to construct interpretable and parsimonious treatment regimes.” Biometrics 71, no. 4 (December 2015): 895–904. https://doi.org/10.1111/biom.12354.Full Text Link to Item
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Schulte, Phillip J., Anastasios A. Tsiatis, Eric B. Laber, and Marie Davidian. “Q- and A-learning Methods for Estimating Optimal Dynamic Treatment Regimes.” Stat Sci 29, no. 4 (November 2014): 640–61. https://doi.org/10.1214/13-STS450.Full Text Link to Item
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Laber, Eric B., Anastasios A. Tsiatis, Marie Davidian, and Shannon T. Holloway. “Discussion of "Combining biomarkers to optimize patient treatment recommendation".” Biometrics 70, no. 3 (September 2014): 707–10. https://doi.org/10.1111/biom.12187.Full Text Link to Item
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Chakraborty, Bibhas, Eric B. Laber, and Ying-Qi Zhao. “Inference about the expected performance of a data-driven dynamic treatment regime.” Clinical Trials (London, England) 11, no. 4 (August 2014): 408–17. https://doi.org/10.1177/1740774514537727.Full Text
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Vock, David M., Anastasios A. Tsiatis, Marie Davidian, Eric B. Laber, Wayne M. Tsuang, C Ashley Finlen Copeland, and Scott M. Palmer. “Assessing the causal effect of organ transplantation on the distribution of residual lifetime.” Biometrics 69, no. 4 (December 2013): 820–29. https://doi.org/10.1111/biom.12084.Full Text Link to Item
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Zhang, Baqun, Anastasios A. Tsiatis, Eric B. Laber, and Marie Davidian. “Robust estimation of optimal dynamic treatment regimes for sequential treatment decisions.” Biometrika 100, no. 3 (2013). https://doi.org/10.1093/biomet/ast014.Full Text Link to Item
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Zhang, Baqun, Anastasios A. Tsiatis, Eric B. Laber, and Marie Davidian. “A robust method for estimating optimal treatment regimes.” Biometrics 68, no. 4 (December 2012): 1010–18. https://doi.org/10.1111/j.1541-0420.2012.01763.x.Full Text Link to Item
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Zhang, Baqun, Anastasios A. Tsiatis, Marie Davidian, Min Zhang, and Eric Laber. “Estimating Optimal Treatment Regimes from a Classification Perspective.” Stat 1, no. 1 (January 1, 2012): 103–14. https://doi.org/10.1002/sta.411.Full Text Link to Item
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- Teaching & Mentoring
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Recent Courses
- COMPSCI 571D: Probabilistic Machine Learning 2023
- ECE 682D: Probabilistic Machine Learning 2023
- STA 561D: Probabilistic Machine Learning 2023
- STA 891: Topics for Preliminary Exam Preparation in Statistical Science 2023
- STA 993: Independent Study 2023
- COMPSCI 571D: Probabilistic Machine Learning 2022
- ECE 682D: Probabilistic Machine Learning 2022
- STA 493: Research Independent Study 2022
- STA 561D: Probabilistic Machine Learning 2022
- STA 693: Research Independent Study 2022
- STA 995: Internship 2022
- COMPSCI 571D: Probabilistic Machine Learning 2021
- ECE 682D: Probabilistic Machine Learning 2021
- STA 493: Research Independent Study 2021
- STA 561D: Probabilistic Machine Learning 2021
- STA 693: Research Independent Study 2021
- STA 790-1: Special Topics in Statistics 2021
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