Published:Journal of Chromatographic Science,
ISSN 0021-9665Volume
38, Number 5, May 2000, pp. 189-194
Taking
Into Account Both Preparation and Injection in High-Performance Liquid Chromatography
Linearity StudiesJérôme
Vial and Alain Jardy
As mentioned
in International Conference on Harmonisation publications, linearity is a principal
parameter in method validation. The most popular statistical tool used is linear
least-squares regression. Contrary to what is still very often practiced, the
correlation coefficient can in no way be considered as an indicator of the fit
quality. There is in fact a test called the “lack-of-fit test” that
enables one to answer the question, “Is the linear model adapted to the
calibration curve?”. However, this test can give erroneous conclusions
when, at each level, several sources of variation for the response are influent.
It often occurs in high-performance liquid chromatography, as shown in a following
example, where the calibration curve is obtained from repeated injections of
repeated dilutions of a parent solution. The lack-of-fit test rejected linearity,
although it was at least questionable. In fact, the reason for a discrepancy
of this kind lies in the presence of a double source of variation: injection
and dilution. It is possible to overcome the problem by mixing a nested ANOVA
with the standard least-square linear regression. As shown in an example, implementing
this methodology for data processing allows one not only to carry out an unbiased
lack-of-fit test but also give estimates of the dispersion introduced respectively
by the preparation and the injection.
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