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ASTM D 6091 Document Information:
Title
Standard Practice for 99 %/95 % Interlaboratory Detection Estimate (IDE) for Analytical Methods with Negligible Calibration Error
ASTM International
Publication Date:
Mar 1, 2007
Scope:
This practice establishes a standard for computing a 99 %/95 %
Interlaboratory Detection Estimate (IDE) and provides guidance
concerning the appropriate use and application. The calculations
involved in this practice can be performed with DQCALC, Microsoft
Excel-based software available from ASTM.2
The IDE is computed to be the lowest concentration at which
there is 90 % confidence that a single measurement from a
laboratory selected from the population of qualified laboratories
represented in an interlaboratory study will have a true detection
probability of at least 95 % and a true nondetection probability of
at least 99 % (when measuring a blank sample).
The fundamental assumption of the collaborative study is that
the media tested, the concentrations tested, and the protocol
followed in the study provide a representative and fair evaluation
of the scope and applicability of the test method as written. When
properly applied, the IDE procedure ensures that the 99 %/95 % IDE
has the following properties:
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.
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.
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).
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, a =
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.
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, ß
= 5 %, at the IDE), with a simultaneous low probability of false
detection (see 1.3.4). Thus, when measuring a sample at the IDE,
the probability of detection would be at least 95 %. To be useful,
this must be demonstrated for the particular matrix being used, and
not just for reagent water.
NOTE 1—The referenced probabilities, a and ß, are key parameters
for risk-based assessment of a detection limit.
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):
Sample Preparation, and calibration standards do not
have to go through sample preparation.
Differences in Analysts, and analysts have little
opportunity to affect calibration results (such as with automated
calibration).
Differences in Laboratories, for whatever reasons,
perhaps difficult to identify and eliminate.
Differences in Instruments (measurement equipment),
which could take the form of differences in manufacturer, model,
hardware, electronics, sampling rate, chemical processing rate,
integration time, software algorithms, internal signal processing
and thresholds, effective sample volume, and contamination
level.
Alternative Data Quality Objectives—Other values fora,
ß, confidence, etc. may be chosen for calculating an IDE; however,
this procedure addresses only the 99 %/95 % IDE.
2 Available from ASTM International Headquarters.
Order Adjunct No. ADJDQCALC. Original adjunct produced in 2007.
Keywords:
- critical limit
- detection
- detection limit
- false detection
- false nondetection
- false positive
- matrix effects
- statistical tolerance limit
- true detection
- true nondetection
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