Validating the bland altman method of agreement

Posted by / 09-Dec-2019 11:11

Validating the bland altman method of agreement

It is identical to a Tukey mean-difference plot Bland and Altman make the point that any two methods that are designed to measure the same parameter (or property) should have good correlation when a set of samples are chosen such that the property to be determined varies considerably.A high correlation for any two methods designed to measure the same property could thus in itself just be a sign that one has chosen a widespread sample. Content Header .feed_item_answer_user.js-wf-loaded . A Bland–Altman plot (Difference plot) in analytical chemistry or biomedicine is a method of data plotting used in analyzing the agreement between two different assays.The Bland-Altman plot (Bland & Altman, 1986) is most likely to be seen in the medical statistics literature.Suppose there are two techniques for measuring some continuously-scaled variable, each having some error, and we want a graphical means to assess whether or not they are comparable.Say one wanted to compare two techniques of measuring some blood factor.

The remaining commands in the example would remain unchanged.(Bland and Altman also discuss the option of using confidence interval bounds, based on the standard error of the mean, for the upper and lower reference lines.) If the two methods are comparable, then differences should be small, with the mean of the differences close to 0, and show no systematic variation with the mean of the two measurements. Likewise, the average of the two measurements (MMEAN, for example) can be computed in the Transform Compute dialog with MMEAN as the target variable and "(A B)/2" as the Numeric Expression.'Small' would be an amount that would be clinically insignificant for the factor being measured. To print descriptive statistics on DIFF, as well as a test of whether DIFF has a mean of 0, run the One-Sample T Test procedure (Analyze One-Sample T Test) with DIFF in the "Test Variable(s)" box. The output for the One-Sample T Test includes the mean and standard deviation of DIFF, along with the standard error of the mean, confidence intervals for the mean (95% by default) and the significance level for the test that the mean of DIFF equals 0. The basic scatterplot can be produced with either the Graph procedure (Graphs Scatter/Dot) or the Chart Builder.If you wanted to keep the previous DIFF and MMEAN variables in the file, you could compute the new log-based difference and mean as LDIFF and LMMEAN, for example, and replace DIFF and MMEAN in the subsequent commands with those new variables.The Bland-Altman plot (also called the Tukey mean difference plot, RA and MA plots, and various other field-specific names) is an XY scatter plot that compares the disagreement, or differences, between two quantitative measurements.

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If the Bland-Altman plot indicates that the variance of DIFF varies across the range of MMEAN, e.g., if the vertical spread of scatter points is much narrower at low values of MMEAN than at high values of MMEAN, Bland and Altman suggest that the researcher calculate the natural logarithms of the two measures (A and B in this example), recalculate the difference and mean measures with new variables and redraw the Bland-Altman plot with the new difference and mean measures.

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