An outlier-resistant indicator of anomalies among inter-laboratory comparison data with associated uncertainty

Abstract

A new robust pairwise statistic, the pairwise median scaled difference (MSD), is proposed for the detection of anomalous location/uncertainty pairs in heteroscedastic interlaboratory study data with associated uncertainties. The distribution for the IID case is presented and approximate critical values for routine use are provided. The determination of observationspecific quantiles and p-values for heteroscedastic data, using parametric bootstrapping, is demonstrated by example. It is shown that the statistic has good power for detecting anomalies compared to a previous pairwise statistic, and offers much greater resistance to multiple outlying values.

Unrecognized Sources of Uncertainties (USU) in Experimental Nuclear Data

“…The ratio r i = (y i − μ)/ (u 2 i + var(μ)), see for example Ref. [18] and similar definitions [19][20][21], is easy to use. A score beyond this definition for an outlier must be documented if values are discarded.…”

Consistency plots: a simple graphical tool for investigating agreement in key comparisons

“…This makes it important to seek alternative graphical tools that do not depend heavily on a reliable reference value. Some procedures have been suggested that address the lack of a reliable reference value by reverting to pairwise comparisons (see, for example, [9,10]), and some can provide graphical output. A plot of the median scaled difference, for example, can provide a useful indicator of location/ uncertainty anomalies without any general location estimate [10].…”

“…Some procedures have been suggested that address the lack of a reliable reference value by reverting to pairwise comparisons (see, for example, [9,10]), and some can provide graphical output. A plot of the median scaled difference, for example, can provide a useful indicator of location/ uncertainty anomalies without any general location estimate [10]. It can, however, be useful to understand the structure and grouping of results in more detail, and for that purpose a more detailed presentation is useful.…”