When necessary, variables were transformed prior to analysis to meet modelling assumptions, and modelling assumptions were validated through visual inspection of model evaluation plots following Zuur et al. ([ 64], page 129).
Following Zuur et al. ([ 64], page 129) modeling assumptions (i.e. normality of residuals and homogeneity of variance) were validated through visual inspection of graphical model evaluation plots.
WinBUGS allows for the most extensive output, including diagnostic plots for model evaluation and plots of the individual random center effects.
There are also differences in the availability of additional tools for model evaluation, such as diagnostic plots.
In addition to common summary statistics (e.g. RMSE, bias, and correlation), several of the many analysis features available in AMET include scatter plots, time series plots, box plot and spatial plots as part of operational model evaluation.
Additional file 1: Supplemental material 1, Figure 6 presents the scatter plots for each model evaluation.
Standard residual plots were used for model evaluation.
Quartz crystal microbalance with dissipation monitoring, viscoelastic model, evaluation of Δ D and Δ f-plot of HSA and calculation of the shear modulus.
Model evaluation was performed using goodness-of-fit plots, as well as the individual weighted residuals (IWRES) and the normalized prediction distribution errors (NPDE) over time.
Results from a model evaluation are shown in Table 2. Scatter-plots of predicted versus monitored concentrations, set against one-to-one lines representing perfect correlation, can be seen in the Supporting Information.
