Comparison of regression techniques for linear calibration

A recently presented regression technique for linear calibration, which is based on a variance component model for univariate quantitative measurement data, is compared with the conventional and far spread regression techniques ordinary least squares regression and weighted least squares regression. The associated statistical models and estimations are represented. Its application is demonstrated at some practical examples. With consideration of special variation causes, like matrix influence or the influence of several operating conditions on the measurement response, it can be shown that the application of the variance component model is an advantage.