Simulation of laboratory errors and their effects on interlaboratory quality-control programs.
The random errors in an analytical method are additive and can be classified into analytical response-dependent and -independent terms. Non-random errors, caused by systematic faults in the analytical procedure, are not always distriguishable from the random errors, but some cases of non-linear assay response and unsuitable standardisation can be studied usefully in models without random error. Interlaboratory quality control programs cannot distinguish systematic and random error until the pattern of results on a number of specimens, or pairs of specimens, can be studied. In this case linear regression analysis is a powerful method for distinguishing different forms of error especially when response-dependent random errors do not predominate. The range of concentrations used for regression whould be as wide as that in which quantitative distinctions are used in clincal diagnosis and treatment. Preliminary reports, of the results on which the regression analysis is based, are most suitably presented on Youden diagrams with paired specimens.
D000704:Analysis of Variance; D002624:Chemistry, Clinical; D011786:Quality Control; D012044:Regression Analysis; D013223:Statistics as Topic