A Bland-Altman plot is a graph used to compare results of experiments in chemistry and medical diagnostics. It compares two measurement techniques by plotting their differences against the mean. It helps researchers determine if the correlation between two methods means the results are the same. Peripheral graphs can also evaluate consistency. Results within plus or minus the standard deviation of 1.96 are believed to have similar outcomes.
A Bland-Altman plot is a graphical measurement often used to compare the results of experiments in analytical chemistry or medical diagnostics. Also called “Tukey mean difference graph”, it can help you analyze the result of methods in chemistry and clinical research. Two measurement techniques are typically compared by plotting values for their differences, in relation to calculations of the mean of both. Typically a standard x and y axis plot is used. If it is an accepted standard being compared against another, the differences can be graphed against just one method.
As new medical diagnostic methods are developed, they are often compared to those in use. The results and outcome of each may differ, but the reason isn’t always clear. A Bland-Altman chart can be used to compare measurements from test equipment, such as that used to measure respiration. It is often used, therefore, to compare methods that are meant to measure the same thing. These methods may be correlated in their results, but sometimes the nature of the sample is the reason.
A Bland-Altman graph usually helps researchers know if the correlation between two methods actually means that the results are the same. The graph is usually made by taking the number of samples in each method compared and converting them into data points. Each sample is shown as a point which is the mean of the two measurements, which is usually represented by the horizontal x-axis. The difference between each is typically indicated on the y-axis; each coordinate is found using a mathematical formula.
Mean differences can also be referenced using horizontal lines on the graph. These typically represent the extent of mathematical agreement between the two methods. The mean difference is usually subtracted by 1.96 times the standard deviation, another mathematical calculation of sample results.
The relationships between the differences in the measurements can be visualized by a Bland-Altman plot; their greatness is also often made apparent. Peripheral graphs can also help evaluate the consistency of measurements. Numbers that are within plus or minus the standard deviation of 1.96 are usually not emphasized; the two methods compared on the Bland-Altman plot, therefore, are generally believed to have similar outcomes in this case. It is also possible to identify repeated results of a method, often with standard deviation calculations, to compare accuracy with the size of what is being measured.
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