Assessment of Bias with Emphasis on Method Comparison
Roger Johnson



Definition of bias - distinct from accuracy, bias is an average deviation from a true value.
• Method comparison - a set of specimens is assayed by both an existing method and the new candidate method, and the
results compared. The following list describes the testing procedures and data handling required in a method comparison
study for the assessment of bias:
&�� Test material
&�� Number and disposition of specimens
&�� Summary of findings
&�� The problem with correlation, and the difference plot
&�� Statistics of difference
&�� Log transformation of the difference plot
&�� Statistics of difference with logs
&�� Linear regression
&�� Deming and Passing-Bablok models
&�� The value of r in linear regression
&�� Choice of statistics
&�� Examples of suitable computer programs
• Acceptable bias criteria are discussed.
• Linearity and recovery - failing either of these criteria should serve as a warning that method comparison data may conceal
an unrecognised bias.
• Finally, consideration of all steps in the assessment of bias is required to determine acceptability or not of the method
comparison.

“Bias is used to express numerically the degree of trueness”, trueness being “the closeness of agreement between the average value obtained from a large series of measurements and the true value”.
“Bias” and “inaccuracy” are often used synonymously. However, contemporary usage by ISO and CLSI1 makes a distinction between these terms: inaccuracy relates to how closely a single measurement agrees with the true value whereas bias relates to how an average of a series of measurements agrees with the true value. In the first case, imprecision contributes to the lack of agreement whereas in the second, imprecision is minimised (ideally removed entirely) by use of an average.

Summary of steps in assessment of bias
1. Criteria of acceptable performance established
2. Comparison of test method with reference method
using patient material ± reference material
3. x-y Plot of data with examination by eye
4. Consideration of difference plot and statistics of
difference
5. Consideration of regression analysis and statistics of
regression
6. Test of interference
7. Test of linearity
8. Test of recovery
9. Judgement of acceptability

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