Bland–Altman plot

Bland–Altman plot, also known as the Bland–Altman difference plot, is a graphical method used to compare two measurements techniques. In the field of biostatistics and health sciences, it is a popular method for assessing the agreement between two clinical measurements or measurement devices. It was introduced by J. Martin Bland and Douglas G. Altman in 1986.

Overview

The Bland–Altman plot offers a visual representation of the difference between two measurements against the average of those measurements. It is particularly useful when comparing new measurement techniques or devices with a gold standard, as it allows for the identification of any systematic bias between the two measurements, as well as any potential outliers.

Methodology

To construct a Bland–Altman plot, the following steps are typically followed:

1. Measure two sets of data on the same subject using the two different methods.
2. Calculate the difference between the two measurements for each subject.
3. Calculate the average of the two measurements for each subject.
4. Plot the differences on the y-axis against the averages on the x-axis.
5. Draw a line at the mean difference (to assess bias) and lines at the mean difference plus and minus 1.96 times the standard deviation of the differences (to assess limits of agreement).

Interpretation

The key to interpreting a Bland–Altman plot lies in examining the spread of the points:

• If the points are randomly scattered without any pattern, it suggests good agreement.
• If the points show a trend, such as increasing difference with an increasing average, it suggests a systematic error between the measurements.
• The mean difference line indicates the average bias; a mean difference far from zero suggests a systematic bias between the two methods.
• The limits of agreement provide an interval within which 95% of the differences between the two methods lie. Narrower limits indicate better agreement.

Applications

Bland–Altman plots are widely used in the medical field to compare different measurement techniques or devices. For example, they may be used to compare a new blood pressure monitor with a standard sphygmomanometer, or to compare laboratory versus bedside glucose measurement techniques.

Advantages and Limitations

Advantages:

• Provides a clear visual representation of agreement.
• Identifies systematic bias and potential outliers.
• Simple to construct and interpret.

Limitations:

• Assumes normal distribution of differences.
• Not suitable for comparing more than two measurement methods at a time.
• Interpretation can be subjective.

Example

File:Bland-Altman plot example.svg

Example of a Bland–Altman plot

An example of a Bland–Altman plot can be seen in the figure to the right. This plot might represent the comparison of two different blood pressure measurement techniques across a range of subjects. The mean difference and limits of agreement are clearly indicated.

See Also

• Measurement error
• Cohen's kappa
• Pearson correlation coefficient
• Intraclass correlation

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