Results of measurements should be independent of the laboratory performing the analysis. Hence the laboratory should document that the method retains statistical control, is without systematic errors and has an acceptably low level of uncertainty. A protocol for the design and interpretation of method evaluation in atomic absorption spectrometry (AAS) using ordinary statistical calculations was applied to determinations of lead and manganese in blood by AAS. The method evaluation design provides information on whether or not the method is in statistical control, i.e., whether the values observed belong to a normal distribution around the mean values. The standard deviation of the normal distribution is an expression of the uncertainty of the method. Using the method evaluation design the estimated uncertainty is truly representative of the methods, i.e., both the withinrun and between-run variations are included. Further, the method evaluation design produces estimates of the magnitude of the systematic error, the limit of detection and the limit of quantification. The application of the mean square error and the square root of the relative mean square error combines the systematic error with the total uncertainty. Hence the square root of the relative mean square error depicts the total analytical error. The systematic error, estimated as the magnitude of the zero point error and the proportional error of the method evaluation functions for Zeeman-effect AAS methods in the determination of manganese, were negligible. The blood lead method was unacceptable at concentrations higher than 200 pg dm-3 owing to the presence of a proportional error. The combined uncertainty of the analytical methods for manganese and lead were 1 .OO and 11.1 pg dm-3, respectively, the limit of detection LODMn=0.2 pg dm-3 and LODpb=12 pg dm-3 at the concentration levels of 11 pg dm-3 of Mn and 72 pg dm+ of Pb. The limit of quantification was LOQMn=2.8 pg dm-3 and LOQpb=33.7 pg dm-3. The design can be conveniently used for quality assurance in AAS analysis and for the characterization of analytical chemical methodology in general.
Methods recommended by the International Standardization Organisation and Eurachem are not satisfactory for the correct estimation of calibration uncertainty. A novel approach is introduced and tested on actual calibration data for the determination of Pb by ICP-AES. The improved calibration uncertainty was verified from independent measurements of the same sample by demonstrating statistical control of analytical results and the absence of bias. The proposed method takes into account uncertainties of the measurement, as well as of the amount of calibrant. It is applicable to all types of calibration data, including cases where linearity can be assumed only over a limited range.
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