ASTM D6091-07(2014)

1.3.1 Routinely Achievable IDE Value—Most laboratories are able to attain the IDE detection performance in routine analyses, using a standard measurement system, at reasonable cost. This property is needed for a detection limit to be practically feasible. Representative laboratories must be included in the data to calculate the IDE.

1.3.2 Routine Sources of Error Accounted For—The IDE should realistically include sources of bias and variation which are common to the measurement process. These sources include, but are not limited to: intrinsic instrument noise, some typical amount of carryover error, plus differences in laboratories, analysts, sample preparation, and instruments.

1.3.3 Avoidable Sources of Error Excluded—The IDE should realistically exclude avoidable sources of bias and variation, that is, those which can reasonably be avoided in routine field measurements. Avoidable sources would include, but are not limited to: modifications to the sample, measurement procedure, or measurement equipment of the validated method, and gross and easily discernible transcription errors (provided there was a way to detect and either correct or eliminate them).

1.3.4 Low Probability of False Detection—The IDE is a true concentration consistent with a measured concentration threshold (critical measured value) that will provide a high probability, 99 %, of true nondetection (a low probability of false detection, α = 1 %). Thus, when measuring a blank sample, the probability of not detecting the analyte would be 99 %. To be useful, this must be demonstrated for the particular matrix being used, and not just for reagent water.

1.3.5 Low Probability of False Nondetection—The IDE should be a true concentration at which there is a high probability, at least 95 %, of true detection (a low probability of false nondetection, β = 5 %, at the IDE), with a simultaneous low probability of false detection (see 1.4 The IDE applies to measurement methods for which calibration error is minor relative to other sources, such as when the dominant source of variation is one of the following (with comment):

1.5 Alternative Data Quality Objectives—Other values forα, β, confidence, etc. may be chosen for calculating an IDE; however, this procedure addresses only the 99 %/95 % IDE.