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Passing & Bablok regression

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Description

Passing & Bablok (1983) have described a linear regression procedure with no special assumptions regarding the distribution of the samples and the measurement errors. The result does not depend on the assignment of the methods (or instruments) to X and Y. The slope B and intercept A are calculated with their 95% confidence interval. These confidence intervals are used to determine whether there is only a chance difference between B and 1 and between A and 0.

Required input

In the dialog box you enter the variables for the two techniques you want to compare.

As an option, you can create 2 graphical windows:

  • A scatter diagram with the regression line (solid line), the confidence interval for the regression line (dashed lines) and identity line (x=y, dotted line)
  • The residuals plot.

Use the Subgroups button if you want to identify subgroups in the scatter diagram and residuals plot. A new dialog box is displayed in which you can select a categorical variable. The graph will display different markers for the different categories in this variable.

Results

When you have completed the dialog box, click the OK button to proceed. The following results will be displayed in a text window.

  • Sample size: the number of (selected) data pairs
  • Summary statistics for both variables: lowest and highest value, mean, median, standard deviation and standard error of the mean
  • The regression equation: the regression equation with the calculated values for A and B according to Passing & Bablok (1983)
  • Intercept A and slope B with 95% confidence interval:

The 95% confidence interval for the intercept A can be used to test the hypothesis that A=0. This hypothesis is accepted if the confidence interval for A contains the value 0. If the hypothesis is rejected, then it is concluded that A is significant different from 0 and both methods differ at least by a constant amount.

The 95% confidence interval for the slope B can be used to test the hypothesis that B=1. This hypothesis is accepted if the confidence interval for B contains the value 1. If the hypothesis is rejected, then it is concluded that B is significant different from 1 and there is at least a proportional difference between the two methods.
  • Test for linearity: the test for linearity is used to evaluate how well a linear model fits the data.

Literature

  • Passing H, Bablok W (1983) A new biometrical procedure for testing the equality of measurements from two different analytical methods. Application of linear regression procedures for method comparison studies in Clinical Chemistry, Part I. J. Clin. Chem. Clin. Biochem., 21:709-720. [Abstract]

See also