Notes on two competing definitions of multivariate sensitivity Original Research Article

In the univariate context analytical figures of merit such as sensitivity play a key role in the selection, validation and optimisation of analytical determinations. In the past, numerous definitions of multivariate sensitivity have been proposed to achieve the same goal in the multivariate context. Two definitions of multivariate sensitivity particularly stand out since they can be shown to relate in a transparent way to other figures of merit such as limit of detection and signal-to-noise ratio: the one due to Lorber and the one due to Bergmann, von Oepen and Zinn (BOZ). Lorberʹs definition has been recently criticised for containing selectivity information: Lorberʹs sensitivity depends on the overlap between the spectra of the analyte and the interferents whereas the BOZ sensitivity is a function of the analyte spectrum only. This paper gives a convenient explanation for this counter-intuitive aspect of Lorberʹs definition and states a recommendation for its application. A practical data set obtained from Prof. Malinowski serves to illustrate theoretical ideas.