If you have two or more measurements per subject for each method, read the Bland-Altman diagram with several measurements by pattern. The Bland-Altman diagram shows four types of data errors. These types are systematic errors (1) (average shift), (2) proportional error (trend), (3) inconsistent variability and (4) excessive or irregular variability. Bland-Altman plots are widely used to assess the agreement between two instruments or two measurement techniques. Bland-Altman plots identify systematic differences between measures (i.e. fixed pre-stress) or potential outliers. The average difference is the estimated distortion, and the SD of the differences measures random fluctuations around this average. If the average value of the difference based on a 1-sample-t test deviates significantly from 0, this means the presence of a solid distortion. If there is a consistent distortion, it can be adjusted by subtracting the average difference from the new method.

It is customary to calculate compliance limits of 95% for each comparison (average difference ± 1.96 standard deviation of the difference), which tells us how much the measurements were more likely in two methods for most people. If the differences in the average± 1.96 SD are not clinically important, the two methods can be interchangeable. The 95% agreement limits can be unreliable estimates of population parameters, especially for small sampling sizes, so it is important to calculate confidence intervals for 95% compliance limits when comparing methods or evaluating repeatability. This can be done by the approximate Bland and Altman method [3] or by more precise methods. [6] Figure 8.2. Comparison of The Methods (n -69) of Busulfan LC-MS/MS (RapidFire) Assay Versus GC-MS (Reference Assay) and Differential Chart (Bland-Altman Plot) In the original Bland-Altman plot (Bland-Altman, 1986), the differences between the two methods are presented in relation to the averages of the two methods. Exercise 15.5. Figure 15.3 shows preoperative levels compared to postoperative plasma silicon levels in the DB5 breast implant. Interpret the results of Bland Altman`s plot. The Bland-Altman diagram can also be used to assess the repeatability of a method by comparing repeated measurements with a single method on a number of subjects. The diagram can then be used to check whether the variability or accuracy of a method is related to the size of the characteristic to be measured.