This approach uses similar data available for all assays using IQC but a slightly different calculation. Rather than assessing bias uncertainty using EQA performance, it is assessed based on reference values and target range data obtainable from reagent and quality control manufacturers.

Random uncertainty is calculated in exactly the same way as for the Single Laboratory validation approach. The difference lies with how the bias uncertainty is calculated.

When using IQC, a target range is available for expected values of the IQC. The range is constructed by the manufacturer. When looked at from an uncertainty perspective the manufacturer is telling us that:

Across a series of lot numbers of reagents, over a defined period of time the expected (measured) value of the IQC is the target value. An associated range around that target may also be provided. However, we must check to see if there is an associated distribution with that value provided. It is simple to assume that the target (and it’s associated range) is determined by repeated measures and therefore normally distributed. However, if a simple range is provided with no other information we may need to assume a rectangular/uniform distribution. This decision is made by the scientist performing the evaluation.

If a target is provided, along with an associated range (expressed in Standard Deviations) we can calculate the standard uncertainty associated with the IQC by taking:

**(Top of the QC range – target mean) / 2**

We can assign the value as the uncertainty associated with the reference we are testing .

This can then be combined with the imprecision (random) uncertainty calculated as before according to the same equation below

**Combined uncertainty = (random uncertainty**^{2}** + reference uncertainty**^{2}**)**^{1/2}

Move onto the “Top-Down” method

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