Eric Laber | Scholars@Duke

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
eric.laber@duke.edu (919) 684-4210

Background
Education, Training, & Certifications
- Ph.D., University of Michigan, Ann Arbor 2011
- M.A., University of Michigan, Ann Arbor 2007
Previous Appointments & Affiliations
- Scholar In Residence of Statistical Science, Statistical Science, Trinity College of Arts & Sciences 2020
Recognition
In the News
- MAY 4, 2023 Duke Today
  
  Duke Awards 44 Distinguished Professorships
- FEB 22, 2021 Duke Research Blog
  
  Increasing Access to Care with the Help of Big Data
- SEP 30, 2020
  
  Eric Laber: From Awe-Inspiring Magic to Problem-Solving Statistics
Research
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
External Relationships
- Amazon
- Chapman Hall/CRC Press
Publications & Artistic Works
Selected Publications
- Academic Articles
  - 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
  - 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
  - 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
  - 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
  - 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
  - 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
  - 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
  - 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
  - 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
  - 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
  - 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
  - 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
  - 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
  - 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
Teaching & Mentoring
Recent Courses

Some information on this profile has been compiled automatically from Duke databases and external sources. (Our About page explains how this works.) If you see a problem with the information, please write to Scholars@Duke and let us know. We will reply promptly.

Education, Training, & Certifications

Previous Appointments & Affiliations

In the News

Selected Grants

External Relationships

Selected Publications

Academic Articles

Recent Courses