UNCERTAINTY OF MEASUREMENT – “BOTTOM-UP” VS “TOP-DOWN”
At the recently concluded Eurachem/PUC training workshop on “Accreditation of analytical, microbiological and medical laboratories – ISO/IEC 17025:2017 and ISO 15189:2012”, the following important pointers were noted during the presentation of Dr Steve Ellison of LGC UK on the to subject : Measurement Uncertainty – “Bottom-up” vs “Top-down”:
Measurement uncertainty assessed in analytical chemistry is either through the use of the Law of Propagation of Uncertainty from uncertainty budgets (or inputs or contributors) as per GUM (bottom-up) method, or adopting the method performance (or validation) data (top-down);
Using the GUM approach with a mathematical model, the laboratory is to assess and sufficiently quantify significant uncertainty contributors in the test procedures. This can be done by (a) using descriptive statistical data through repeated experiments (Type A), or (b) any other means, such as certificates of analysis by a third party, theory or professional judgement (Type B);
It has been stated that testing laboratories tend to underestimate measurement uncertainty using the GUM method in almost measurement fields, as one cannot comprehensively identify and quantify all important uncertainty inputs;
Use of any one of the top-down approaches with the use of validation data is a better bet in the evaluation of measurement uncertainty because the actual dispersion of test results in extended experiments can be observed; the major uncertainty source data can come from (a) long term precision (intermediate reproducibility), (b) bias uncertainty based on reliable certified reference materials, and (c ) any other additional important effects which are not part of the method’s mathematical equation;
By definition, uncertainty is a range which includes the true value. Therefore, any significant bias should not be ignored.
Empirical methods are operationally defined. In the top-down approach, relevant reference material should be used to estimate laboratory bias as an input of uncertainty. In this case, only matrix bias is to be taken care of and method bias is not relevant.
Eurachem opines that the bottom-up GUM method is appropriate for metrology laboratories, whilst the top-down approaches are best for testing laboratories.
I would like to share some of the ideas picked up at the 2-day Eurachem / Pancyprian Union of Chemists (PUC) joint training workshop on 20-21 February 2020, titled “Accreditation of analytical, microbiological and medical laboratories – ISO/IEC 17025:2017 and ISO 15189:2012”, after flying all the way from Singapore to Nicosia of Cyprus via a stop-over at Istanbul.
Today, let’s see whether there is a requirement for an expression of uncertainty in qualitative analysis. In other words, are there quantitative reports of uncertainties in qualitative test results?
Qualitative chemical and microbiological testing usually fall under the following binary classifications with two outcomes only:
Pass/Fail for a targeted measurand
Positive/Negative
Presence/Absence
“Above” or “Below” a limit
Red or Yellow colour
Classification into ranges (<2; 2 – 5; 5 – 10;>10)
