Pulmonary Translational Biostatistics and Bioinformatics Core in the Division of Pulmonary & Critical Care at the University of Colorado Anschutz Medical Campus. He is a passionate statistical collaborator whose research interests span a range of specialized areas, including clinical trials, infectious disease epidemiology, machine learning, model selection, interpretability, statistical computation, best practices for statistical collaboration, and missing data. He is also an active member of the Center for Innovative Design & Analysis, which provides a broad range of statistical expertise for researchers both locally and across the nation. Dr. Peterson obtained his BA in Economics at St. Olaf College, and his PhD in Biostatistics from the University of Iowa.
What's in your data? Insight
"The novelty—I am always learning new and interesting things, and understanding the world in new ways."
"A biostatistician has broad appeal in the sciences. We can help solve a lot of issues with study design and we can aid in the forming and interpretation of the results. This makes us an indispensable component of science in general."
Areas of Expertise
- Model selection
- Interpretability in machine learning
- Statistical computation/software
- Best practices for statistical collaboration
- Missing data
Education, Licensure & Certifications
- PhD, Biostatistics, University of Iowa, 2019
- MS, Biostatistics, University of Iowa, 2016
- BA, Economics, St. Olaf College, 2014
Awards
- Milford E. Barnes Award, University of Iowa, 2019
- Best Poster Award, International Biometrics Conference, 2020; Best Paper Award, Journal of Applied Statistics
- Early Career Award, Association for Clinical and Translational Statisticians, 2021
- Best Contributed Session Award, American Statistical Association Statistical Consulting Section (Joint Statistical Meetings), 2023.
Courses
- BIOS 6621 Statistical Consulting I
- BIOS 6602 Applied Biostatistics II
- BIOS 7722 Model Selection
Publications and Presentations
- Peterson RA, Cavanaugh JE. Ranked sparsity: a cogent regularization framework for selecting and estimating feature interactions and polynomials. AStA Adv Stat Anal. 2022 Jan 25:106:427-454.
- Peterson RA. Finding optimal normalization transformations via bestNormalize. The R Journal. 2021 Jun 07: 13(1):310-329.
- Peterson RA. A Simple Aggregation Rule for Penalized Regression Coefficients after Multiple Imputation. J. Data. Sci. 2021 Jan:19(1):1-14.
- Peterson RA, Cavanaugh JE. Ordered quantile normalization: a semiparametric transformation built for the cross-validation era. Journal of Applied Statistics. 2019 June 15: 1-16.
- Peterson RA, Hochheimer CJ, Grunwald GK, Johnson RL, Wood C, Sammel MD; Reaping what you SOW: Guidelines and Strategies for Writing Scopes of Work for Statistical Consulting. Stat. 2022:e496.