▪Switch between compartment models of different complexity and fit. The parameters are either maintained for each model type, or converted, according to the Model conversion setting in the Extras panel.
▪The results of the different fits are stored in the Model History which can be used for easy switching and for the results comparison per region.
▪Check the residuals for judging model adequacy.
▪Check the different criteria on the Details tab (Schwartz Criterion SC, Akaike Information Criterion AIC, Model Selection Criterion MSC) to decide whether a more complex model is supported by the data.
▪Check for parameter identifiability. As an indicator of the parameter identifiability standard errors (%SE) are returned from the fit. They should remain limited for all relevant parameters. Additionally, Monte Carlo simulations can be performed to obtain distribution statistics of the parameter estimates.
▪If justified by physiology, try to improve the stability of parameter estimation by enforcing common parameters among regions in a coupled fitting procedure.
▪Compare the outcome of compartment models with that of other models, such as reference models or graphical plots.