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Analytical bias

The polarography of sulphones has been fairly extensively studied, sometimes with an analytical bias and sometimes with more theoretical interest. It is generally accepted that a two-electron reduction takes place, to sulphinate ... [Pg.108]

Figure 4.22. Correlation of assay values for components A and B, for three dosage levels of A, with 10 samples per group. The comer symbols indicate the 10% specification limits for each component. For manual injection (left panel) only relative standard deviations of 1-2% are found, but no correlation. Automatic injection (right panel) has a lower intrinsic relative standard deviation, but the data are smeared out along the proportionality line because no internal standard was used to correct for variability of the injected volume. The proportionality line does not go through the comers of the specification box because component B is either somewhat overdosed (2.4%). analytical bias, or because an interference results in too high area readings for B. The... Figure 4.22. Correlation of assay values for components A and B, for three dosage levels of A, with 10 samples per group. The comer symbols indicate the 10% specification limits for each component. For manual injection (left panel) only relative standard deviations of 1-2% are found, but no correlation. Automatic injection (right panel) has a lower intrinsic relative standard deviation, but the data are smeared out along the proportionality line because no internal standard was used to correct for variability of the injected volume. The proportionality line does not go through the comers of the specification box because component B is either somewhat overdosed (2.4%). analytical bias, or because an interference results in too high area readings for B. The...
DEGRAD STABILjcIs Section 1.8.4 The analysis of stability reports often suffers from the fact that the data for each batch of product is scrutinized in isolation, which then results in a see-no-evil attitude if the numerical values are within specifications. The analyst is in a good position to first compare all results gained under one calibration (usually a day s worth of work) irrespective of the products/projects affected, and then also check the performance of the calibration samples against experience, see control charts, Section 1.8.4. In this way, any analytical bias of the day will stand out. For this purpose a change in format from a Time-on-Stability to a Calendar Time depiction is of help. [Pg.395]

Ripley, B. D., and Tompson, M., Regression Techniques for the Detection of Analytical Bias, Analyst 112, April 1987, 377-383. [Pg.407]

Identification of sources of analytical bias in method development and method validation is another very important application of reference materials in geochemical laboratories. USGS applied simplex optimization in establishing the best measurement conditions when the ICP-AES method was introduced as a substitute for AAS in the rapid rock procedure for major oxide determinations (Leary et al. 1982). The optimized measurement parameters were then validated by analyzing a number of USGS rock reference samples for which reference values had been established first by classical analyses. Similar optimization of an ICP-AES procedure for a number of trace elements was validated by the analysis of U S G S manganese nodule P-i (Montaser et al. 1984). [Pg.224]

Once initial analyses are completed, random samples are sent from SGS to ActLabs for check assays, to establish precision (repeatability) and analytical bias. Additionally, coarse sample rejects are chosen at random and sent to ActLabs for preparation and analysis, to check the accuracy and repeatability of the original sample preparation. A further check on SGS Lab precision is conducted by renumbering pulps and re-submission from ActLab to SGS for analysis. Tournigan monitors quality assurance by plotting and analyzing the data, as received, and activates re-assaying of sample batches that do not meet predetermined standards. [Pg.475]

Figure 4. Factor two (B, Cu, Fe, Mn, Ni, Na) vs. Factor one (As, Ba, COD, Li, pH, Sr) factor score plot for WA and WS wells only. Analytical bias identified. Figure 4. Factor two (B, Cu, Fe, Mn, Ni, Na) vs. Factor one (As, Ba, COD, Li, pH, Sr) factor score plot for WA and WS wells only. Analytical bias identified.
Keywords Traceability Laboratory medicine Biological variation Analytical bias Quality assurance Standardization Reference measurement system Joint Committee on Traceability for Laboratory Medicine... [Pg.128]

RM certification is the whole process of obtaining the property values and their uncertainties, which includes homogeneity testing, stability testing, and RM characterization [5]. ISO Guide 35 [1] requires one to show that the value of such a certified property does not exhibit a systematic error specific to a method or to a laboratory. By widespread opinion, correctness of analytical results is an obvious prerequisite for the RM characterization in contrast to stability and homogeneity studies in which analytical bias is acceptable [5]. [Pg.269]

Potential analytical bias, vital effects, and calibration issues all complicate interpretation of the records shown in Figure 10. Measured benthic foraminiferal Mg/Ca ratios in site 747 (Billups and Schrag, 2002) are in general higher than in coeval samples from the composite record of... [Pg.3414]

Lear et al. (2000) implying warmer temperatures. The sense of this offset is unexpected given the high latitude of site 747. A systematic analytical bias between the two data sets is possible because... [Pg.3415]

E453 Kroll, M.H., Ruddel, M. and Elin, R.J. (1988). Analytical bias for cholesterol and the percent of the population deemed at risk for coronary heart disease. Clin. Chem. 34, 2009-2011. [Pg.296]

Klee GG, Schryver PG, Kisabeth RM. Analytic bias specifications based on die analysis of effects on performance of medical guidelines. Scand J Clin Lab Invest 1999 59 509-12. [Pg.349]

In addition to imprecision, goals for bias should also be considered. Gowans et related the allowable bias to the width of the reference interval, which is determined by the combined within- and between-subject biological variation in addition to the analytical variation. On the basis of considerations concerning the included percentage in an interval in the presence of analytical bias, it was suggested that ... [Pg.362]

Klee G. A conceptual model for establishing tolerance limits for analytical bias and imprecision based on variations in population test distributions. Clin Chim Acta 1997 260 175-88. [Pg.405]

Petersen PH, de Verdier C-H, Groth T, Fraser CG, Blaabjerg O, Horder M. The influence of analytical bias on diagnostic misclassifications. Clin Chim Acta 1997 260 189-206. [Pg.406]

Analytical variations may increase the number of results in a healthy population outside a previously established reference interval A positive analytical bias increases the number of high values and a negative bias decreases the number below the lower reference limit. It is possible to link the maximum tolerable analytical bias to biological variability. The relationship below is derived on the assumption that the maximum acceptable bias is less than one quarter of the sum of the intraindividual and interindividuai variations within a population. [Pg.470]

By substituting different factors in the above formula different targeted analytical biases can be identified. If less analytical bias is deemed to be appropriate (e.g., one fifth of the total biological variation instead of one quarter), 0.20 would be substituted for 0.25. It has been suggested that analytical precision should be less than one half of the mean intrain-dividuai variation CVa = <0.50 CVj), Total error is derived from the smn of imprecision and bias. From the formula above... [Pg.470]

Other formulas have been used to determine quality specifications for bias. Generally, analytical bias should be less than one quarter of interindividuai biological variation. [Pg.470]

Changes in analytical bias directly shift the distribution of the patient test values. If the elevated values on a test are associated with specific clinical actions, then the shifts in analytical bias can notably alter the number of patients having test values that exceed the action limit. For example, for a serum calcium assay with an action limit of lO.i mg/dL, an upward bias of 0.2 mg/dL changes the number of patients subjected to further investigation from 6.5% to 15.0%. Similarly, analytical shifts in other critical analytes can cause notable clinical problems, such as false elevations of prostate-specific antigen values triggering prostate ultrasound examinations and biopsies and false elevation of TSH triggering additional thyroid examinations. These small analytical shifts can have major downstream effects on healthcare costs. [Pg.513]

Klee GG. Tolerance limits for short-term analytical bias and analytical imprecision derived from clinical assay specificity. Clin Chem 1993 39 1514-8. [Pg.525]

Smith FA, Kroft SH. Optimal procedures for detecting analytic bias using patient samples. Am J Clin Pathol 1997 108 254-68. [Pg.526]


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See also in sourсe #XX -- [ Pg.470 ]




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