ISSN:
1612-1112
Keywords:
Chromatographic data
;
Internal-standard calibration
;
Least-squares regression
;
Ratio-data homocedasticity
;
Ratio-data normality
Source:
Springer Online Journal Archives 1860-2000
Topics:
Chemistry and Pharmacology
Notes:
Summary Because the quotient of two normal variables does not fit a normal distribution and tends to be heterocedastic, the use of internal-standard least-squares regression on data obtained from such ratios gives a calibration function which can result in inaccurate determination of the concentration of analyte in a sample. In this work we have studied simulated situations in which area-ratios are fitted to a normal distribution. It is shown that the least-squares model is inappropriate when the ordinate data-ratios are not normally distributed, and some recommendations are proposed to ensure both normality and homocedasticity of the quotient of analyte/internal-standard signals. Finally, GC-MS separation and quantification of nine fatty acids by use of an internal standard are used for experimental verification of the conclusions reached.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF02467494
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