• To compare the differences between the two samples, regardless of their averages, it is best to consider the ratio between the pairs of measurements.  The log transformation (base 2) of the measurements prior to the analysis makes it possible to use the standard approach; Thus, the action will be given by the following equation: A Bland-Altman diagram (differential diagram) in analytical chemistry or biomedicine is a method of data representation that is used in the analysis of the agreement between two different sets. It is identical to a tube of average difference Tukey, the name under which it is known in other areas, but it was popularized in the medical statistics of J. Martin Bland and Douglas G. Altman.   Readers are referred to the following documents, which contain measures of concordance: diagram showing a correlation between hemoglobin measurements using two data methods presented in Tables 3 and 1. The dotted line is a trend line (the line of the smallest squares) by the observed values, and the correlation coefficient is 0.98. However, the different points are very far from the perfect line of correspondence (solid black line) – (observed chord [Po] – expected agreement [Pe] / (1)). 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  or by more precise methods.  Qureshi et al. compared the degree of prostatic adenocarcinoma assessed by seven pathologists using a standard system (Gleason score).  The agreement between each pathologist and the initial relationship and between the pairs of pathologists was determined with Cohen`s Kappa. That is a useful example. However, we think that the gleasons score is an ordinal variable, weighted kappa might have been a more appropriate choice between the measurements, which refers to the degree of adequacy between two (or more) measurement rates.

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