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Amanda Koepke (Fed)

Amanda Koepke graduated from Texas Tech University in 2008 with a B.A. in Mathematics and Statistics and a B.A. in Psychology. In 2014 she received her Ph.D. in Statistics from the University of Washington. She completed a year-long postdoctoral research fellowship at the Fred Hutchinson Cancer Research Center in Seattle before joining the Statistical Engineering Division at NIST in 2015.

Amanda's current research interests include Bayesian analysis, meta-analysis/interlaboratory studies, and stochastic modeling.


Technical Areas of Research and Consulting:

  • Bayesian analysis
  • Statistical modeling
  • Uncertainty analysis
  • Markov chain Monte Carlo methods, including particle filters and other approximate methods
  • Consensus values




  • 2015 Young Investigator Award from the Statistics in Epidemiology Section of the American Statistical Association.


Decision Tree for Key Comparisons

Antonio Possolo, Amanda Koepke, David Newton, Michael R. Winchester
This contribution describes a Decision Tree intended to guide the selection of statistical models and data reduction procedures in key comparisons (KCs). The
Created June 5, 2018, Updated December 8, 2022