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The SIMCA modelling, allowed for the discrimination between chromophores, with both spectral sets, i.e. excitation and emission, while using less pre-processing treatments.
While VP spectroscopy enabled the acquisition of absorbance data for a broad concentration range, PLS modelling allowed for the differentiation between the protein species.
Mixed effects modelling allowed for the addition of interindividual and interoccasion variability in model parameters, in addition to residual variability.
Forward stepwise regression modelling allowed for adjustment of variables significant at the bivariate level (see Table 3).
Adaptation of techniques previously used in business consumer behaviour modelling, allowed for the development of insights into health behaviour in a cost-effective manner without extensive and costly surveys or cohort studies.
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The modelling allows for the design of the optimum conditions for an ultrafast spectroscopy experiment.
Adding the latent class modelling allows for further improvement of model fit.
Piecewise growth curve modelling allows for estimation of different growth curves (slopes) for different time periods.
Ensemble-models allowed for the visualization of prediction uncertainty.
The simulation model allowed for a prospective analysis of the future effects of the legislation.
The use of these models allowed for the identification of the best and worst performing countries.
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