The Analyst · 1995 · 97 citations · 12 references
Natural SciencesQuality ManagementAnalytical ChemistryMethod ValidationQuality AssuranceData QualitySample CollectionSampling DesignSampling MethodsSampling TechniquesSampling TheoryAccuracyAnalytical Test DataProficiency TestingReference MaterialsSampling Bias AssessmentSampling Data QualitySampling Quality AssessmentSampling Quality Control
A comprehensive set of concepts and practices exists for analytical data quality, but sampling lacks a comparable framework. The paper explores the feasibility of developing a complete quality framework for sampling. The study examines sampling analogues of trueness, bias, accuracy error, precision, uncertainty, traceability, fitness for purpose, reference materials, collaborative trials, proficiency tests, and internal quality control. It demonstrates that nearly all analytical quality concepts can be adapted to sampling with only minor adjustments.
There is now a self-consistent and almost complete body of concepts and practices relating to the quality of analytical data. The need for quality in sampling is also well recognized but there has been no comparable development of an over-all approach or, in some aspects, even of a basic methodology. This paper discusses the prospects for a complete approach to quality in sampling. It shows that virtually all of the concepts and practices used in analysis can be adapted, with only a slight change of detail, for application to sampling. Topics considered include the sampling analogues of trueness, bias, accuracy error, precision, uncertainty, traceability, fitness for purpose, reference materials, collaborative trials, proficiency tests and internal quality control.
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