Abstract
This chapter concerns statistical concepts and procedures that are applicable to diagnostic testing performed in the clinical laboratory. Three important laboratory issues are addressed: the estimation of analytical imprecision, the design of an effective laboratory quality control strategy, and the establishment of population reference ranges. These three topics were selected because each demonstrates a valuable statistical principle. Estimation of analytical imprecision highlights the important role of study design. Evaluating laboratory quality control strategies emphasizes the importance of choosing appropriate statistical models. The estimation of population reference ranges demonstrates that there can be many different approaches to developing good statistical estimators.
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References
Neter, J., Kutner, M. H., Wasserman, W., and Nachtsheim, C. J. (1996) Applied Linear Statistical Models, 4th ed. Homewood, Irwin.
Clinical and Laboratory Standards Institute. (2004) Evaluation of Precision Performance of Quantitative Measurement Methods; Approved Guideline—Second Edition. EP5-A2. Villanova, Clinical and Laboratory Standards Institute.
Littell, R. C., Milliken, G. A., Stroup, W. W., Wolfinger, R. D., and Schabenberger, O. (2006) SAS for Mixed Models, 2nd ed. Cary, SAS Institute.
Satterthwaite, F. E. (1946) An approximate distribution of estimates of variance components. Biometrics 2, 110–114.
Clinical and Laboratory Standard Institute. (1999) Statistical Quality Control for Quantitative Measurements: Principles and Definitions; Approved Guideline—Second Edition. C24-A2. Villanova, Clinical and Laboratory Standards Institute.
Westgard, J. O., and Klee, G. G. (2006) Quality management. In: Burtis, C. A., Ashwood, E. R., and Bruns, D. E., eds. Tietz Textbook of Clinical Chemistry and Molecular Diagnostics, 4th ed. St. Louis, Elsevier Saunders, pp. 485–532.
Parvin, C. A. (1997) Quality-control (QC) performance measures and the QC planning process. Clin. Chem. 43, 602–607.
Linnet, K. (1991) Mean and variance rules are more powerful or selective than quality control rules based on individual values. J. Clin. Chem. Clin. Biochem. 29, 417–424.
Parvin, C. A. (1993) New insight into the comparative power of quality-control rules that use control observations within a single analytical run. Clin. Chem. 39, 440–447.
Parvin, C. A., and Gronowski, A. M. (1997) Effect of analytical run length on quality-control (QC) performance and the QC planning process. Clin. Chem. 43, 2149–2154.
Parvin, C. A. (1991) Estimating the performance characteristics of quality-control procedures when error persists until detection. Clin. Chem. 37, 1720–1724.
Clinical and Laboratory Standards Institute. (2000) How to Define and Determine Reference Intervals in the Clinical Laboratory; Approved Guideline—Second Edition. C28-A2. Villanova, Clinical and Laboratory Standards Institute.
David, H. A., and Nagaraja, H. N. (2003) Order Statistics, 3rd ed. New York, John Wiley & Sons.
Parrish, R. S. (1990) Comparison of quantile estimators in normal sampling. Biometrics 46, 247–257.
Harrell, F. E., and Davis, C. E. (1982) A new distribution-free quantile estimator. Biometrika 69, 635–640.
Solberg, H. E. (2006) Establishment and use of reference values. In: Burtis, C. A., Ashwood, E. R., and Bruns, D. E. eds. Tietz Textbook of Clinical Chemistry and Molecular Diagnostics, 4th ed. St. Louis, Elsevier Saunders, pp. 425–448.
Beran, R., and Hall, P. (1993) Interpolated nonparametric prediction intervals and confidence intervals. J. Roy. Statist. Soc. B 55, 643–652.
Harris, E. K., and Boyd, J. C. (1995) Statistical Bases of Reference Values in Laboratory Medicine. New York, Marcel Dekker.
Reed, A. H., Henry, R. J., and Mason, W. B. (1971) Influence of statistical method used on the resulting estimate of normal range. Clin. Chem. 17, 275–284.
Horn, P. S., and Pesce, A. J. (2003) Reference intervals: an update. Clin. Chim. Acta. 334, 5–23.
Linnet, K. (1987) Two-stage transformation systems for normalization of reference distributions evaluated. Clin. Chem. 33, 381–386.
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© 2007 Humana Press Inc., Totowa, NJ
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Parvin, C.A. (2007). Statistical Topics in the Laboratory Sciences. In: Ambrosius, W.T. (eds) Topics in Biostatistics. Methods in Molecular Biology™, vol 404. Humana Press. https://doi.org/10.1007/978-1-59745-530-5_18
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DOI: https://doi.org/10.1007/978-1-59745-530-5_18
Publisher Name: Humana Press
Print ISBN: 978-1-58829-531-6
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