The new generation of measurement

Rogers, L. B.

doi:10.1021/ac00212a001

Cited by 2 publications

(2 citation statements)

References 26 publications

(18 reference statements)

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“…) (The term 'detection limit' (DL) is synonymous.) Random error reported as coefficient of variation ranges from about 25 percent to 100 percent at the Limit of Detection (Ingle,1974;Hunt and Wilson, 1986;Winefordner and Ward, 1980;Rogers, 1990 and one sample matrix. Different procedures and sample matrices will have different limits.…”

Section: Limit Of Detection Conventionsmentioning

confidence: 99%

CONFLICTING PERSPECTWES ABOUT DETECTION LIMITS AND ABOUT THE CENSORING OF ENVIRONMENTAL DATA¹

Clark¹,

Whitfield

1994

J American Water Resour Assoc

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Current conventions for reporting analytical results from environmental samples brings the objectives of laboratory scientists into conflict with those of environmental scientists. The objective of chemical analyses is to provide estimates of the true composition of samples. Reported results must reflect the analytical uncertainty. Current conventions require left‐censoring of those results below the Limit of Detection. The objective of statistical interpretation of environmental data is to provide estimates of the characteristics of ecosystems. Such statistical analyses are often confounded by left‐censoring of analytical results. We review the different points of view and propose a compromise which recognizes these conflicting perspectives.

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Section: Limit Of Detection Conventionsmentioning

confidence: 99%

CONFLICTING PERSPECTWES ABOUT DETECTION LIMITS AND ABOUT THE CENSORING OF ENVIRONMENTAL DATA¹

Clark¹,

Whitfield

1994

J American Water Resour Assoc

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“…The possibility of misidentification is ever present and is of continuing concern to analysts. [1][2][3][4][5] In general, a qualitative identification cannot be guaranteed to be correct even when the analyst making the identification follows all the canons of best practice. Interpretation of the results must accordingly take the relevant uncertainties into account.…”

mentioning

confidence: 99%

PerspectiveQuantifying uncertainty in qualitative analysis

Ellison¹,

Gregory²

1998

Analyst

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The feasibility of adopting a consistent approach to the expression of uncertainties relating to identification is discussed. It is argued that qualitative analysis can be viewed as a classification problem, that it is at least as important as quantitative analysis and that inferences drawn from qualitative tests should take relevant uncertainties into account. A brief review of systems of reasoning under uncertainty is presented, and it is concluded that Bayes' theorem provides the most suitable framework, providing for combination of separate items of evidence and implicitly allowing for both false positive and false negative probabilities in a single parameter. The chemical significance and practical evaluation of relevant probabilities are considered, and the applications and reporting of 'identification certainty' figures are discussed.

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The new generation of measurement

Cited by 2 publications

References 26 publications

CONFLICTING PERSPECTWES ABOUT DETECTION LIMITS AND ABOUT THE CENSORING OF ENVIRONMENTAL DATA¹

CONFLICTING PERSPECTWES ABOUT DETECTION LIMITS AND ABOUT THE CENSORING OF ENVIRONMENTAL DATA¹

PerspectiveQuantifying uncertainty in qualitative analysis

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The new generation of measurement

Cited by 2 publications

References 26 publications

CONFLICTING PERSPECTWES ABOUT DETECTION LIMITS AND ABOUT THE CENSORING OF ENVIRONMENTAL DATA1

CONFLICTING PERSPECTWES ABOUT DETECTION LIMITS AND ABOUT THE CENSORING OF ENVIRONMENTAL DATA1

PerspectiveQuantifying uncertainty in qualitative analysis

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About

CONFLICTING PERSPECTWES ABOUT DETECTION LIMITS AND ABOUT THE CENSORING OF ENVIRONMENTAL DATA¹

CONFLICTING PERSPECTWES ABOUT DETECTION LIMITS AND ABOUT THE CENSORING OF ENVIRONMENTAL DATA¹