Eric Haupt, ScM

Eric Haupt works as a research associate providing informatics support to an oncology clinical trials program in Southern California. He has a Master of Science in Epidemiology from Johns Hopkins University and is most interested in clinical trial design and biomarker qualification.

All articles by Eric Haupt, ScM

Researchers developed a novel Bayesian adaptive randomization method that maximizes efficiency by fo

General Oncology

Bayesian Adaptive Randomization: A Q&A With Brian M. Alexander MD, PhD

Eric Haupt, ScM

April 24, 2017

Researchers developed a novel Bayesian adaptive randomization method that maximizes efficiency by focusing the algorithm to reduce uncertainty within patient-treatment baskets.

Researchers interpreting results from studies using adaptive randomization must be aware of assumpti

Breast Cancer

Adaptive Randomization and the I-SPY 2 Trial Platform

Eric Haupt, ScM

October 26, 2016

Researchers interpreting results from studies using adaptive randomization must be aware of assumptions made during study.

Readers should look for “anything that adds uncertainty to the analysis."

Lung Cancer

Statistical Significance, Uncertainty, and KEYNOTE-010

Eric Haupt, ScM

July 26, 2016

Readers should look for “anything that adds uncertainty to the analysis, including uncertainty in the measurements, differences in dropout rates among arms, missing data, and how they were handled in the analysis.”

Next post in Lung Cancer

Eric Haupt, ScM

All articles by Eric Haupt, ScM

Bayesian Adaptive Randomization: A Q&A With Brian M. Alexander MD, PhD

Adaptive Randomization and the I-SPY 2 Trial Platform

Statistical Significance, Uncertainty, and KEYNOTE-010

Vaccines, Immunotherapy May Enhance Survival of Patients With NSCLC