2012
DOI: 10.1007/s00769-011-0871-1
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The quality coefficient as performance assessment parameter of straight line calibration curves in relationship with the number of calibration points

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Cited by 14 publications
(10 citation statements)
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“…Larger deviations present at larger concentrations tend to influence (weight) the regression line more than smaller deviations associated with smaller concentrations, and thus the accuracy in the lower end of the range is impaired. It is therefore very convenient [122][123][124] to analyse the plotted data and to make sure that they cover uniformly (approximately equally spaced) the entire range of signal response from the instrument (85). Data should be measured at random (to avoid confusing non-linearity with drift).…”
Section: Calibration Graphs: the Question Of Intercept Or Non-interceptmentioning
confidence: 99%
“…Larger deviations present at larger concentrations tend to influence (weight) the regression line more than smaller deviations associated with smaller concentrations, and thus the accuracy in the lower end of the range is impaired. It is therefore very convenient [122][123][124] to analyse the plotted data and to make sure that they cover uniformly (approximately equally spaced) the entire range of signal response from the instrument (85). Data should be measured at random (to avoid confusing non-linearity with drift).…”
Section: Calibration Graphs: the Question Of Intercept Or Non-interceptmentioning
confidence: 99%
“…Table 2 summarizes for the twelve solvents the R² values and the quality coefficients. For all curves the g values were below 0.01 [21]. From this table it can clearly been concluded that the calibration curves for all components are linear within the chosen concentration ranges.…”
Section: Linearity Of the Calibration Linementioning
confidence: 73%
“…De Beer et al 122 have presented new mathematical models which demonstrate the extent to which the number of calibration points defines the value of the quality coefficient for different values of 'g' (a parameter which controls the symmetry of the prediction interval of the abscissa value obtained from the confidence intervals around the curve). The result of this appeared to be that it was much harder to predict the quality of the calibration than is generally thought, and the authors provided an elaborated example of how to improve the quality of the calibration by lowering the g-value beneath a critical value.…”
Section: Chemometricsmentioning
confidence: 99%