The concept 'sensitivity' has multiple and sometimes incompatible usages and definitions, as they can be found in the scientific and technical literature. A strategy is proposed toward a conceptual framework in which sensitivity is qualitatively intended as a feature of a black box behavior and quantitatively is defined according to specific evaluation types (interval/ratio, ordinal, nominal) for both deterministic and stochastic behaviors. The proposed formal definitions characterize stochastic sensitivity as constituted of "effective" and "confounding" components, that can be simultaneously present and contribute to a desirable and unwanted increment of global sensitivity respectively. Two examples taken from the context of imaging systems and image-based measuring systems, in which sensitivity is computed in presence of non-negligible uncertainty sources, provide some hints on the usefulness of the proposed framework.
Mencattini, A., Mari, L. (2015). A conceptual framework for concept definition in measurement: The case of 'sensitivity'. MEASUREMENT, 72, 77-87 [10.1016/j.measurement.2015.04.030].
A conceptual framework for concept definition in measurement: The case of 'sensitivity'
MENCATTINI, ARIANNA;
2015-01-01
Abstract
The concept 'sensitivity' has multiple and sometimes incompatible usages and definitions, as they can be found in the scientific and technical literature. A strategy is proposed toward a conceptual framework in which sensitivity is qualitatively intended as a feature of a black box behavior and quantitatively is defined according to specific evaluation types (interval/ratio, ordinal, nominal) for both deterministic and stochastic behaviors. The proposed formal definitions characterize stochastic sensitivity as constituted of "effective" and "confounding" components, that can be simultaneously present and contribute to a desirable and unwanted increment of global sensitivity respectively. Two examples taken from the context of imaging systems and image-based measuring systems, in which sensitivity is computed in presence of non-negligible uncertainty sources, provide some hints on the usefulness of the proposed framework.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.