Eric B. Laber

Zhen Li, Eric B. Laber, Robert T. Brigantic, 2018, 2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME).

A Batch, Off-Policy, Actor-Critic Algorithm for Optimizing the Average Reward pdf

Susan A. Murphy, Richard S. Sutton, Hamid Reza Maei, 2016, ArXiv.

Bayesian Nonparametric Policy Search With Application to Periodontal Recall Intervals

Dipankar Bandyopadhyay, Brian J. Reich, Eric B. Laber, 2018, Journal of the American Statistical Association.

Informing sequential clinical decision-making through reinforcement learning: an empirical study

Joelle Pineau, Susan A. Murphy, Daniel J. Lizotte, 2010, Machine Learning.

Set‐valued dynamic treatment regimes for competing outcomes

Daniel J. Lizotte, Eric B. Laber, Bradley Ferguson, 2012, Biometrics.

Global forensic geolocation with deep neural networks pdf

Matthew J. Gebert, Krishna Pacifici, Brian J. Reich, 2019, Journal of the Royal Statistical Society: Series C (Applied Statistics).

Estimating optimal treatment regimes from a classification perspective

Min Zhang, Anastasios A. Tsiatis, Eric B. Laber, 2016 .

A spatiotemporal recommendation engine for malaria control.

Brian J. Reich, Eric B. Laber, Qian Guan, 2020, Biostatistics.

ST810 Advanced Computing Lecture 23: Sparse Regression

Eric B. Laber, Hua Zhou, Hua Zhou, 2013 .

Estimating Dynamic Treatment Regimes in Mobile Health Using V-Learning

Michael R. Kosorok, Eric B. Laber, Daniel J. Luckett, 2016, Journal of the American Statistical Association.

Sufficient Markov Decision Processes with Alternating Deep Neural Networks

Eric B. Laber, Katie Witkiewitz, Longshaokan Wang, 2017, 1704.07531.

Dynamic Treatment Regimes

Anastasios A. Tsiatis, Eric B. Laber, Marie Davidian, 2019 .

Multiple Decision Treatment Regimes: Overview

Anastasios A. Tsiatis, Eric B. Laber, Marie Davidian, 2019 .

Multi-Objective Markov Decision Processes for Data-Driven Decision Support

Daniel J. Lizotte, Eric B. Laber, D. Lizotte, 2016, J. Mach. Learn. Res..

Optimal Dynamic Treatment Regimes

Anastasios A. Tsiatis, Eric B. Laber, Marie Davidian, 2016 .

ST810 Advanced Computing Lecture 22: Dynamic Programming

Eric B. Laber, Hua Zhou, 2013 .

High-Dimensional Precision Medicine From Patient-Derived Xenografts pdf

Michael R. Kosorok, Yufeng Liu, Eric B. Laber, 2019, Journal of the American Statistical Association.

15. Evaluating Personalized Treatment Regimes

Min Qian, Eric B. Laber, Min Qian, 2017 .

Small Sample Inference for Generalization Error in Classification Using the CUD Bound

Susan A. Murphy, Eric B. Laber, S. Murphy, 2008, UAI.

Single Decision Treatment Regimes: Additional Methods

Anastasios A. Tsiatis, Eric B. Laber, Marie Davidian, 2019 .

Regimes Based on Time-to-Event Outcomes

Anastasios A. Tsiatis, Eric B. Laber, Marie Davidian, 2019 .

Efficient augmentation and relaxation learning for individualized treatment rules using observational data

Yang Ning, Eric B. Laber, Ying-Qi Zhao, 2019, J. Mach. Learn. Res..

Hierarchical Continuous Time Hidden Markov Model, with Application in Zero-Inflated Accelerometer Data

Ana-Maria Staicu, Eric B. Laber, Zekun Xu, 2018, 1812.01162.

Optimal Multiple Decision Treatment Regimes

Anastasios A. Tsiatis, Eric B. Laber, Marie Davidian, 2019 .

Estimation and Optimization of Composite Outcomes

Michael R. Kosorok, Eric B. Laber, Daniel J. Luckett, 2017, J. Mach. Learn. Res..

A Robust Method for Estimating Optimal Treatment Regimes

Eric B. Laber, M. Davidian, A. Tsiatis, 2012, Biometrics.

Statistical Inference in Dynamic Treatment Regimes

Eric B. Laber, D. Lizotte, S. Murphy, 2010, 1006.5831.

Dynamic treatment regimes: technical challenges and applications.

Eric B. Laber, D. Lizotte, S. Murphy, 2014, Electronic journal of statistics.

Interactive Q-Learning for Quantiles

Eric B. Laber, L. Stefanski, K. Linn, 2017, Journal of the American Statistical Association.

Using pilot data to size a two‐arm randomized trial to find a nearly optimal personalized treatment strategy

Rui Song, Donglin Zeng, Marie Davidian, 2016, Statistics in medicine.

On sparse representation for optimal individualized treatment selection with penalized outcome weighted learning

Donglin Zeng, Eric B. Laber, Eric Laber, 2015, Stat.

Who will benefit from antidepressants in the acute treatment of bipolar depression? A reanalysis of the STEP-BD study by Sachs et al. 2007, using Q-learning

Eric B. Laber, I. Lipkovich, Fan Wu, 2015, International Journal of Bipolar Disorders.

Interactive model building for Q-learning.

Eric B. Laber, Eric B Laber, Kristin A Linn, 2014, Biometrika.

Tree-based methods for individualized treatment regimes.

Eric B. Laber, Y. Q. Zhao, 2015, Biometrika.

Use of standardized bioinformatics for the analysis of fungal DNA signatures applied to sample provenance.

Eric B. Laber, Noah Fierer, Eric B Laber, 2020, Forensic science international.

Fungi Identify the Geographic Origin of Dust Samples

Eric B. Laber, Neal S. Grantham, B. Reich, 2015, PloS one.

Functional Feature Construction for Individualized Treatment Regimes

Eric B. Laber, A. Staicu, 2018, Journal of the American Statistical Association.

Estimation of optimal dynamic treatment regimes

Eric B. Laber, Ying‐Qi Zhao, 2014, Clinical trials.

Missing Data and Uncertainty in Batch Reinforcement Learning

Eric B. Laber, D. Lizotte, S. Murphy, 2008 .

Interpretable Dynamic Treatment Regimes

Marie Davidian, Eric B. Laber, Anastasios A Tsiatis, 2016, Journal of the American Statistical Association.

Doubly Robust Learning for Estimating Individualized Treatment with Censored Data.

Eric B. Laber, D Zeng, M Yuan, 2015, Biometrika.

Interactive Q-learning for Probabilities and Quantiles

Kristin A. Linn, Eric B. Laber, Leonard A. Stefanski, 2014, 1407.3414.

Statistical Significance and the Dichotomization of Evidence: The Relevance of the ASA Statement on Statistical Significance and p-Values for Statisticians

Kerby Shedden, Eric B. Laber, Eric B Laber, 2017, Journal of the American Statistical Association.

Adaptive confidence intervals for non-smooth functionals

Eric B. Laber, 2011 .

Comment

Eric B. Laber, B. Reich, Qian Guan, 2016, Journal of the American Statistical Association.

Note on Thompson sampling for large decision problems

Eric B. Laber, Z. Li, K. Pacifici, 2019, 1905.04735.

Rejoinder of “Dynamic treatment regimes: Technical challenges and applications”

Susan A. Murphy, Daniel J. Lizotte, Eric B. Laber, 2014, Electronic Journal of Statistics.

Sample Size Calculations for SMARTs

Eric B. Laber, M. Kosorok, M. Davidian, 2019, 1906.06646.

Identifying optimal dosage regimes under safety constraints: An application to long term opioid treatment of chronic pain

Eric B. Laber, I. Lipkovich, Fan Wu, 2018, Statistics in medicine.

Telehealth and racial disparities in colorectal cancer screening: A pilot study of how virtual clinician characteristics influence screening intentions

Janice L. Krieger, Eric B. Laber, M. Davidian, 2022, Journal of Clinical and Translational Science.

Personalized Evaluation of Biomarker Value: A Cost-Benefit Perspective

Eric B. Laber, Ying Huang, 2014, Statistics in biosciences.

Chapter 15: Estimation of dynamic treatment regimes for complex outcomes: Balancing benefits and risks

Eric B. Laber, L. Stefanski, K. Linn, 2015 .

Variable selection using pseudo-variables

Eric B. Laber, L. Stefanski, Wenhao Hu, 2018, 1804.01201.

A multiple imputation strategy for sequential multiple assignment randomized trials.

Joelle Pineau, Susan A Murphy, Eric B. Laber, 2017, Statistics in medicine.

Double-Blind Randomized Placebo-Controlled Trials in the Treatment of Affective Disorders: Problems and Alternatives

Eric B. Laber, I. Lipkovich, E. Severus, 2015, Current Treatment Options in Psychiatry.

Overcoming missing data in a sequential , multiple assignment , randomized clinical trial of patients with schizophrenia

Eric B. Laber, Joelle Pineau, S. Murphy, 2022 .

A Pilot Study Examining the Efficacy of Delivering Colorectal Cancer Screening Messages via Virtual Health Assistants.

Janice L. Krieger, Eric B. Laber, Benjamin C. Lok, 2021, American journal of preventive medicine.

Predictors of Response to 4-Aminopyridine in Chronic Canine Spinal Cord Injury.

Eric B. Laber, N. Olby, Melissa J Lewis, 2019, Journal of neurotrauma.

Estimating optimal treatment regimes from a classification perspective

Eric B. Laber, M. Davidian, A. Tsiatis, 2012, Stat.

Title Optimal treatment allocations in space and time for on-line control of an emerging infectious disease Permalink

Eric B. Laber, B. Reich, K. Pacifici, 2022 .

Evaluation of a Stepped-Care eHealth HIV Prevention Program for Diverse Adolescent Men Who Have Sex With Men: Protocol for a Hybrid Type 1 Effectiveness Implementation Trial of SMART

Eric B. Laber, David A. Moskowitz, B. Mustanski, 2020, JMIR research protocols.

Small Sample Prediction Intervals for the Test Error In Classification

Eric B. Laber, S. Murphy, 2008 .

Rejoinder

Eric B. Laber, S. Murphy, 2011 .

Inference for change-plane regression

Eric B. Laber, Rui Song, M. Banerjee, 2022, 2206.06140.

Interim Monitoring of Sequential Multiple Assignment Randomized Trials Using Partial Information

Eric B. Laber, M. Davidian, Cole Manschot, 2022, 2209.06306.

Understanding heterogeneity of responses to, and optimizing clinical efficacy of, exercise training in older adults: NIH NIA Workshop summary

Eric B. Laber, K. Moreau, N. LeBrasseur, 2022, GeroScience.

Characterizing expected benefits of biomarkers in treatment selection.

Eric B. Laber, H. Janes, Ying Huang, 2015, Biostatistics.

Sizing a phase II trial to find a nearly optimal personalized treatment strategy

Eric B. Laber, M. Kosorok, M. Davidian, 2014 .

Evaluating Personalized Treatment Regimes

Eric B. Laber, Min Qian, 2019 .

Associations Between Anesthetic Variables and Functional Outcome in Dogs With Thoracolumbar Intervertebral Disk Extrusion Undergoing Decompressive Hemilaminectomy

Eric B. Laber, K. Muñana, H. Volk, 2017, Journal of veterinary internal medicine.

The ecology of microscopic life in household dust

Krishna Pacifici, Eric B. Laber, Noah Fierer, 2015, Proceedings of the Royal Society B: Biological Sciences.

Inference about the expected performance of a data-driven dynamic treatment regime

Eric B. Laber, Bibhas Chakraborty, Eric B Laber, 2014, Clinical trials.

Precision Medicine.

Eric B. Laber, M. Kosorok, 2019, Annual review of statistics and its application.

Optimal Treatment Regimes: A Review and Empirical Comparison

Eric B. Laber, Z. Li, Jie Chen, 2023, International Statistical Review.

Optimal treatment allocations in space and time for on‐line control of an emerging infectious disease

John M Drake, Krishna Pacifici, Eric B. Laber, 2018, Journal of the Royal Statistical Society. Series C, Applied statistics.

Using decision lists to construct interpretable and parsimonious treatment regimes

Marie Davidian, Eric B. Laber, Eric B Laber, 2015, Biometrics.

New Statistical Learning Methods for Estimating Optimal Dynamic Treatment Regimes

Donglin Zeng, Michael R Kosorok, Eric B. Laber, 2015, Journal of the American Statistical Association.

Robust estimation of optimal dynamic treatment regimes for sequential treatment decisions.

Marie Davidian, Eric B. Laber, Anastasios A Tsiatis, 2013, Biometrika.

Inference for Optimal Dynamic Treatment Regimes Using an Adaptive m‐Out‐of‐n Bootstrap Scheme

Yingqi Zhao, Eric B. Laber, Bibhas Chakraborty, 2013, Biometrics.

Estimating optimal treatment regimes from a classification perspective

Min Zhang, Marie Davidian, Eric B. Laber, 2012, Stat.

Optimizing delivery of a behavioral pain intervention in cancer patients using a sequential multiple assignment randomized trial SMART.

Eric B. Laber, Caroline S. Dorfman, Christine M Nuñez, 2017, Contemporary clinical trials.

Evaluation of a Stepped-Care eHealth HIV Prevention Program for Diverse Adolescent Men Who Have Sex With Men: Protocol for a Hybrid Type 1 Effectiveness Implementation Trial of SMART (Preprint)

Eric B. Laber, David A. Moskowitz, B. Mustanski, 2020 .

Personalized Evaluation of Biomarker Value: A Cost-Benefit Perspective

Eric B. Laber, Ying Huang, 2014, Statistics in biosciences.

Adaptive Confidence Intervals for the Test Error in Classification

Susan A Murphy, Eric B. Laber, Eric B Laber, 2011, Journal of the American Statistical Association.

Incorporating Patient Preferences into Estimation of Optimal Individualized Treatment Rules

Michael R Kosorok, Eric B. Laber, Eric B Laber, 2018, Biometrics.

Hand grip strength predicts mortality and quality of life in heart failure: Insights from the Singapore Cohort of Patients with Advanced Heart Failure: Grip strength predicts mortality and quality of life in heart failure.

Eric B. Laber, C. Malhotra, R. Mentz, 2022, Journal of cardiac failure.

iqLearn: Interactive Q-Learning in R.

Eric B. Laber, Eric B Laber, Kristin A Linn, 2015, Journal of statistical software.

Sequential Knockoffs for Variable Selection in Reinforcement Learning

Eric B. Laber, C. Shi, Zhengling Qi, 2023, ArXiv.

Interim monitoring of sequential multiple assignment randomized trials using partial information.

Eric B. Laber, M. Davidian, Cole Manschot, 2022, Biometrics.

Behavioral cancer pain intervention dosing: results of a Sequential Multiple Assignment Randomized Trial.

Eric B. Laber, M. Davidian, F. Keefe, 2023, Pain.

Discussion of “Combining biomarkers to optimize patient treatment recommendation”

Marie Davidian, Eric B. Laber, Anastasios A Tsiatis, 2014, Biometrics.

Creating an mHealth App for Colorectal Cancer Screening: User-Centered Design Approach

Janice L. Krieger, Benjamin Lok, Eric B. Laber, 2019, JMIR human factors.

A SMART approach to optimizing delivery of an mHealth intervention among cancer survivors with posttraumatic stress symptoms.

Eric B. Laber, J. Owen, T. Somers, 2021, Contemporary clinical trials.

Dynamic treatment regimes, past, present, and future: A conversation with experts

Eric B. Laber, M. Davidian, 2017, Statistical methods in medical research.

Deep Spatial Q-Learning for Infectious Disease Control

Ethan X. Fang, Eric B. Laber, Jesse Clifton, 2023, Journal of Agricultural, Biological and Environmental Statistics.

Estimation and Optimization of Composite Outcomes

Eric B. Laber, Daniel J. Luckett, M. Kosorok, 2017, J. Mach. Learn. Res..

Exploratory Analysis of Practical Trial Data for Informing the Individualization Of Treatment

Eric B. Laber, D. Lizotte, S. Murphy, 2009 .

A Robust Method for Estimating Optimal Treatment Regimes

Eric B. Laber, M. Davidian, A. Tsiatis, 2012, Biometrics.

Cost-Effectiveness Analysis Evaluating Delivery Strategies for Pain Coping Skills Training in Women with Breast Cancer.

Eric B. Laber, M. Davidian, F. Keefe, 2023, The journal of pain.

Set‐valued dynamic treatment regimes for competing outcomes

Eric B. Laber, D. Lizotte, Bradley Ferguson, 2012, Biometrics.

Inference for Optimal Dynamic Treatment Regimes Using an Adaptive m‐Out‐of‐n Bootstrap Scheme

Eric B. Laber, B. Chakraborty, Ying‐Qi Zhao, 2013, Biometrics.

Effectiveness of the SMART Sex Ed program among 13–18 year old English and Spanish speaking adolescent men who have sex with men

Eric B. Laber, David A. Moskowitz, B. Mustanski, 2022, AIDS and Behavior.