Recognizing Structural Nonidentifiability: When Experiments Do Not Provide Information About Important Parameters and Misleading Models Can Still Have Great Fit
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DOI: 10.1111/risa.13386
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- Philip J. Schmidt, 2015. "Norovirus Dose–Response: Are Currently Available Data Informative Enough to Determine How Susceptible Humans Are to Infection from a Single Virus?," Risk Analysis, John Wiley & Sons, vol. 35(7), pages 1364-1383, July.
- Tim Maiwald & Helge Hass & Bernhard Steiert & Joep Vanlier & Raphael Engesser & Andreas Raue & Friederike Kipkeew & Hans H Bock & Daniel Kaschek & Clemens Kreutz & Jens Timmer, 2016. "Driving the Model to Its Limit: Profile Likelihood Based Model Reduction," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-18, September.
- Philip J. Schmidt & Katarina D. M. Pintar & Aamir M. Fazil & Edward Topp, 2013. "Harnessing the Theoretical Foundations of the Exponential and Beta‐Poisson Dose‐Response Models to Quantify Parameter Uncertainty Using Markov Chain Monte Carlo," Risk Analysis, John Wiley & Sons, vol. 33(9), pages 1677-1693, September.
- Mark P Little & Wolfgang F Heidenreich & Guangquan Li, 2010. "Parameter Identifiability and Redundancy: Theoretical Considerations," PLOS ONE, Public Library of Science, vol. 5(1), pages 1-6, January.
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