5 papers
Backward Bayesian Outcome Weighted Learning
Emmanuel M. Rockwell, Michael R. Kosorok, Nikki L. B. Freeman
A central objective of precision medicine is learning optimal dynamic treatment regimes (DTRs) from data. Classification-based methods, like outcome weighted learning (OWL) for sin…
Statistical Design and Rationale of the Biomarkers for Evaluating Spine Treatments (BEST) Trial
John Sperger, Kelley M. Kidwell, Matthew C. Mauck +16
Chronic low back pain (cLBP) is a prevalent condition with profound impacts on functioning and quality of life. While multiple evidence-based treatments exist, they all have modest…
Optimal individualized treatment regimes for survival data with competing risks
Christina W. Zhou, Nikki L. B. Freeman, Katharine L. McGinigle +1
Precision medicine leverages patient heterogeneity to estimate individualized treatment regimens, formalized, data-driven approaches designed to match patients with optimal treatme…
Bayesian Outcome Weighted Learning
Sophia Yazzourh, Nikki L. B. Freeman
One of the primary goals of statistical precision medicine is to learn optimal individualized treatment rules (ITRs). The classification-based, or machine learning-based, approach…
Dynamic treatment regime characterization via value function surrogate with an application to partial compliance
Nikki L. B. Freeman, Sydney E. Browder, Katharine L. McGinigle +1
Precision medicine is a promising framework for generating evidence to improve health and health care. Yet, a gap persists between the ever-growing number of statistical precision…