October 19th, 2021

The tool you choose depends on the intended use.

Parts 1 Through 3 Recap
In Part 1 (July 2021), when I started this series on test method comparison, I provided an overview of several basic precision concepts:

Accuracy
Bias
Correlation coefficient
Regression curve
Repeatability
Reproducibility

In Part 2 (August 2021) I explained why it is unrealistic to expect correlation coefficients between two methods, each based on a different parameter (e.g., CFU mL-1 and gene…

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September 20th, 2021

The tool you choose depends on the intended use.

 

Agreement

In August, I discussed the concept of attribute score agreement between two test parameters. Before continuing to the next part of my discussion, I’ll use a Venn diagram to further illustrate this concept. Figure 1 shows the respective data sets obtained by two test parameters – ATP-bioburden and culturable bacterial bioburden (bacterial CFU mL-1). The blue and red circles, respectively, represent the ATP and…

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August 18th, 2021

The tool you choose depends on the intended use.

A Bit More About Relative Bias

In my last post I introduced the concept of relative bias. I wrote that unless there is a reference standard against which a measurement can be compared, only relative bias – the difference between test results obtained by different methods – can be assessed. In my example, I compared the results of two test methods for determining the concentration of end-use diluted metalworking fluids (MWF). …

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July 29th, 2021

The tool you choose depends on the intended use.

 

Culture Versus Non-Culture Test Methods

History

There is a false impression among microbiologists and non-microbiologists alike that because culture testing has been around since the mid-19th century, it is a reference method (I’m come back to the reference method concept in a bit). The first quantitative culture-based method – the heterotrophic plate count (HPC) first appeared in Standard Methods for the Examination of…

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June 24th, 2021

Refresher

In my March 2021 article, I began a discussion of root cause analysis (RCA). In that article I reviewed the importance of defining the problem clearly, precisely, and accurately; and using brainstorming tools to identify cause and effect networks or paths. Starting with my April 2021 article I used a case study to illustrate the basic RCA process steps. That post focused on defining current knowledge and defining knowledge gaps. Last month, I covered the next two steps: closing…

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