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Measurement Uncertainty in Microbiology

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Testing laboratories wishing to comply with the requirements of ISO/IEC 17025:1999 need to estimate uncertainty of measurement for their quantitative methods. Many microbiological laboratories have had procedures available for monitoring variability in duplicate results generated by laboratory analysts for some time. These procedures, however, do not necessarily include all possible contributions to uncertainty in the calculations. Procedures for estimating microbiological method uncertainty, based on the Poisson distribution, have been published but, at times, the procedures can either underestimate uncertainty or require laboratories to undertake considerable experimental studies and more complex statistical calculations. This paper proposes procedures for estimating uncertainty of measurement in microbiology, whereby routine laboratory quality control data can be analyzed with simple statistical equations. The approaches used in these procedures are also applied to published data and examples, demonstrating that essentially equivalent results can be obtained with these procedures.

Document Type: Research Article

Affiliations: Lynne I. Forster Training & Consulting Services, PO Box 15847, New Lynn, Auckland, New Zealand

Publication date: 2003-09-01

More about this publication?
  • The Journal of AOAC INTERNATIONAL publishes refereed papers and reviews in the fields of chemical, biological and toxicological analytical chemistry for the purpose of showcasing the most precise, accurate and sensitive methods for analysis of foods, food additives, supplements and contaminants, cosmetics, drugs, toxins, hazardous substances, pesticides, feeds, fertilizers and the environment available at that point in time. The scope of the Journal includes unpublished original research describing new analytical methods, techniques and applications; improved approaches to sampling, both in the field and the laboratory; better methods of preparing samples for analysis; collaborative studies substantiating the performance of a given method; statistical techniques for evaluating data. The Journal will also publish other articles of general interest to its audience, e.g., technical communications; cautionary notes; comments on techniques, apparatus, and reagents.
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