A two-component model for measurement error in analytical chemistry

David M Rocke, Stefan Lorenzato

Research output: Contribution to journalArticlepeer-review

156 Scopus citations


In this article, we propose and test a new model for measurement error in analytical chemistry. Often, the standard deviation of analytical errors is assumed to increase proportionally to the concentration of the analyte, a model that cannot be used for very low concentrations. For near-zero amounts, the standard deviation is often assumed constant, which does not apply to larger quantities. Neither model applies across the full range of concentrations of an analyte. By positing two error components, one additive and one multiplicative, we obtain a model that exhibits sensible behavior at both low and high concentration levels. We use maximum likelihood estimation and apply the technique to toluene by gas-chromatography/mass-spectrometry and cadmium by atomic absorption spectroscopy.

Original languageEnglish (US)
Pages (from-to)176-184
Number of pages9
Issue number2
StatePublished - 1995


  • Atomic absorption spectroscopy (AAS)
  • Coefficient of variation
  • Detection limit
  • Gas-chromatography/mass-spectrometry (GC/MS)
  • Maximum likelihood
  • Quantitation level

ASJC Scopus subject areas

  • Modeling and Simulation
  • Applied Mathematics
  • Statistics and Probability


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