Bland-Altman plot with multiple measurements per subject
Create a Bland-Altman plot for method comparison when there is more than one measurement per subject with each laboratory method.
The Bland-Altman plot (Bland & Altman, 1986, 1999, 2007), or difference plot, is a graphical method to compare two measurements techniques. In this graphical method the differences (or alternatively the ratios) between the two techniques are plotted against the averages of the two techniques. Alternatively (Krouwer, 2008) the differences can be plotted against one of the two methods, if this method is a reference or "gold standard" method.
Horizontal lines are drawn at the mean difference, and at the limits of agreement, which are defined as the mean difference plus and minus 1.96 times the standard deviation of the differences. If the differences within mean ± 1.96 SD are not clinically important, the two methods may be used interchangeably.
The plot is useful to reveal a relationship between the differences and the averages, to look for any systematic biases and to identify possible outliers.
How to enter data
This procedure requires that you have your data organized like in the following example (data from Bland & Altman, 2007):
There is one column for subject identification (Subject) and one column for the measurements for each method (RV and IC).
If you have your data organized in a different format, such as the data for the multiple measurements in different columns, you can use the Stack columns tool to reorganize your data (see also the Stack columns worked example).
This is the graph in the True value is constant in each subject model:
In the True value is constant in each subject model (see Bland & Altman, 2007) there is only one marker for each subject in the graph, and the marker size is relative to the number of observations for the subject. The number of markers is equal to the number of subjects.
In the alternative model, where the True value varies, there is one marker for each observation pair: