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Also, the slope from the MLFR was much lower than in the equivalent OLR model, and the intercept was much higher.
The intercept in the MLFR model significantly differed to zero at P<0.001, in contrast to the application of OLR where significant differences were inconsistent.
The application of MLFR does not lead to these problems.
We found contrasting estimates of the regression coefficients of models based on OLR and the MLFR approach when comparing the two methods (Table 5).
Consequently, an MLFR approach will not have its full advantage over using OLR.
Importantly, this points to the need to further investigate in what circumstances is applying OLR acceptable or whether the errors-in-both-variables problem is sufficient to necessitate modelling the MLFR.
For researchers to construct harmonisation models based on analysis of the MLFR, they will need archived soil samples and sufficient historical documentation to enable them to obtain data on precision and bias.
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