Bland and Altman point out that two methods for measuring the same parameter (or property) should have a good correlation when a group of samples is selected, so the property to be determined varies greatly. A high correlation for two different methods designed to measure the same property could therefore in itself only be a sign that a widespread sample has been chosen. A high correlation does not necessarily mean that there is a good agreement between the two methods. The limits of convergence approach was introduced in 1983 by the English statisticians Martin Bland and Douglas Altman. The method became popular according to the authors` 1986 article in The Lancet. This second article is one of the most cited statistical articles since it has been cited more than 30,000 times. Bland Altman diagrams are widely used to assess the concordance between two different instruments or two measurement techniques. Bland Altman diagrams identify systematic differences between measurements (i.e. solid distortions) and potential outliers. The mean difference is the estimated distortion, and the SD of differences measures random variations around this mean. If the mean value of the difference is significantly 0 based on a test of 1 sample t, this indicates the existence of a solid distortion.

If there is a consistent distortion, it can be adjusted by subtracting the mean difference from the new method. It is customary to calculate 95% of match limits for each comparison (mean difference ± 1.96 standard deviation of the difference), which tells us to what extent measurements with two methods were more likely for most individuals. If the differences in the mean ± 1.96 SD are not clinically important, the two methods can be used interchangeably. . . .