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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

Frequency Ratio Measurements with 18-Digit Accuracy Using a Network of Optical Clocks

Kyle Beloy, Martha I. Bodine, Tobias B. Bothwell, Samuel M. Brewer, Sarah L. Bromley, Jwo-Sy Chen, Jean-Daniel Deschenes, Scott Diddams, Robert J. Fasano, Tara Fortier, Youssef Hassan, David Hume, Dhruv Kedar, Colin J. Kennedy, Isaac Kader, Amanda Koepke, David Leibrandt, Holly Leopardi, Andrew Ludlow, Will McGrew, William Milner, Daniele Nicolodi, Eric Oelker, Tom Parker, John M. Robinson, Stefania Romisch, Stefan A. Schaeffer, Jeffrey Sherman, Laura C. Sinclair, Lindsay I. Sonderhouse, William C. Swann, Jian Yao, Jun Ye, Xiaogang Zhang
Atomic clocks occupy a unique position in measurement science, exhibiting higher accuracy than any other measurement standard and underpinning six out of seven
Created June 5, 2018, Updated June 15, 2021