Accreditation and Quality Assurance

, Volume 9, Issue 8, pp 457–463

The statistical basis of standardization designs for diagnostic assays

General Paper

Abstract

Accuracy and long-term quality of laboratory diagnostic assays depend critically on the standardization process. In this note we review statistically typical procedures and designs used in standardization. Issues of practical relevance such as the number of systems, runs, and replicates to be involved in the standardization design, and quality control aspects, are addressed.

Keywords

Standardization design Value assignment Analysis of variance Outlier analysis 

References

  1. 1.
    Passing H, Müller B, Brettschneider H (1981) The importance of a blind control in the establishment of assigned values in control sera, J Clin Chem Clin Biochem, 19:1137–1144Google Scholar
  2. 2.
    Passing H (1981) The inadequacy of normal distribution models for the establishment of assigned values in control sera, J Clin Chem Clin Biochem, 19:1145–1151Google Scholar
  3. 3.
    Passing H (1981) Comparison of three distribution free procedures in the establishment of assigned values in control sera. J Clin Chem Clin Biochem, 19:1153–1166Google Scholar
  4. 4.
    Passing H, Bablok W, Brettschneider H (1981) An optimized design for the establishment of assigned values in control sera, J Clin Chem Clin Biochem, 19:1167–1179Google Scholar
  5. 5.
    Vangel MG, Rukhin AL (1999) Maximum likelihood analysis for heteroscedastic one-way random effects ANOVA in interlaboratory studies, Biometrics, 55:129–136Google Scholar
  6. 6.
    Rukhin AL, Biggerstaff BJ, Vangel MG (2000) Restricted maximum-likelihood estimation of a common mean and the Mandel–Paul algorithm. J Stat Planning Inference, 83:319–330Google Scholar
  7. 7.
    Neter J, Wassermann W, Kutner M (1985) Applied linear statistical models, 2nd edn, Richard D. Irwin, Inc., HomewoodGoogle Scholar
  8. 8.
    Searle RS, Casella G, McCulloch C (1992) Variance components, 1st edn, Wiley, New YorkGoogle Scholar
  9. 9.
    Konnert A (2003) Linear random effects models with applications in clinical chemistry (diploma thesis). University of UlmGoogle Scholar
  10. 10.
    Burdick RK, Graybill FA (1992) Confidence intervals on variance components 1st edn, Dekker, Inc., New YorkGoogle Scholar
  11. 11.
    Dietrich CF (1991) Uncertainty, calibration and probability the statistics of scientific and industrial measurement, 2nd edn, Adam Hilger, BristolGoogle Scholar
  12. 12.
  13. 13.
    Wellmann J, Gather U (2000) Identification of outliers in a one-way random effects model (technical report). University of Dortmund Department of Statistics, University of Münster Institute of Epidemiology and Social MedicineGoogle Scholar

Copyright information

© Springer-Verlag 2004

Authors and Affiliations

  1. 1.Faculty of Mathematics and EconomicsUniversity Ulm and Biometry Roche Diagnostics GmbHPenzbergGermany
  2. 2.Biometry, Roche Diagnostics GmbHPenzbergGermany

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