Bland-Altman plot

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Bland-Altman plot
Bland-Altman plot

In analytical chemistry and biostatistics, a Bland-Altman plot is a method of data plotting used in analysing the agreement between two different assays. It is identical to a Tukey mean-difference plot, which is what it is still known as in other fields, but was popularised in medical statistics by Bland and Altman.[1][2]

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[edit] Agreement vs correlation

Bland and Altman make the point that any two methods that are designed to measure the same parameter (or property) will have a good correlation when a set of samples are chosen such that the property to be determined vary a lot between them. A high correlation for any two methods designed to measure the same property is thus in itself is just a sign that one has chosen a wide spread sample. A high correlation does not automatically imply that there is good agreement between the two methods.

[edit] How to construct a Bland-Altman plot

Consider a set of n samples (for example, objects of unknown volume). Both assays (for example, different methods of volume measurement) are performed on each sample, resulting in 2n data points. Each of the n samples is then represented on the graph by assigning the mean of the two measurements as the abscissa (x-axis) value, and the difference between the two values as the ordinate (y-axis) value.

Hence, the Cartesian coordinates of a given sample S with values of S1 and S2 determined by the two assays is

S(x,y)=\left( \frac{S_1+S_2}{2},(S_1-S_2) \right)

[edit] Application

One primary application of the Bland-Altman plot is to compare two clinical measurements that each provide some errors in their measure.[3] It can also be used to compare a new measurement technique or method with a gold standard even so the interest of the Bland-Altman plot is contested in this particular case because the error pertains to the sole new measure. See Analyse-it or MedCalc for software providing Bland-Altman plots.

[edit] References

  1. ^ Altman DG, Bland JM (1983). "Measurement in medicine: the analysis of method comparison studies". Statistician 32: 307-317. 
  2. ^ Bland JM, Altman DG (1986). "Statistical methods for assessing agreement between two methods of clinical measurement". Lancet 1 (8476): 307-10. 
  3. ^ Hanneman SK (2008). "Design, analysis, and interpretation of method-comparison studies". AACN Advanced Critical Care 19: 223-234. 
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