Measurement uncertainty with nested mixed effect models

Measurement uncertainty in experiments is receiving increasing interest among practitioners both for quantitative and qualitative evaluations. Applications may be found, for example, to compare experiments run in different laboratories, to certify the precision of gauges used in the masurement process or to measure uncertainty in a classification process, i.e. when objects are qualitatively evaluated by appraisers. In this paper, after having briefly presented how to measure uncertainty using gauge repeatability and reproducibility studies, we focus on a problem quite relevant for practitioners: how to deal with the presence of correlation among ‘replications’. This issue is common to many food/agriculture experiments. By a modification of a nested mixed effect design, we describe the impact of dependencies among replications on measurement capability.