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Calibration was assessed using a calibration curve generated by plotting the model-predicted 5-year and 10-year survival probabilities against the observed probability, as calculated by the Kaplan-Meier method.

By plotting the diffusion model and the zero and the first order models, it was found that the zero order had the highest correlation coefficient.

The mean CD4 count and percentage evolution were depicted by plotting the mixed model predictions.

One way to objectively choose (alpha ^2) is by plotting the norm of the model vector, (||{varvec{m}}||/{text {max}}(||{varvec{m}}||)) (individually normalized to the range between 0 and 1 for better comparison between different orbits) versus the norm of data misfit, (||{varvec{Gm}}-{varvec{d^{{mathrm{obs}}}}}||) for various values of the regularization parameter (alpha ^2).

Internal validation of the 13-state Markov model was done by plotting the posterior predictive (i.e. modelled) distribution of proportions against the data with their 95% classical Wald confidence intervals, indicating the close fit.

We investigated non-proportionality in our models by plotting the Schoenfeld residuals and by correlating the residuals for each model with time for each covariate with a two-sided χ test.

We visualized this model by plotting the relationship between the probability of death and SAPS-3 score for different categories of chloremia (Fig. 1).

By plotting the log likelihood of this model, segments with significant effects were found.

We studied the cross coverage between each pair of models by plotting the corresponding coverage values with different numbers of predicted active compounds, n.

The fit of the proportional hazards model was checked visually by plotting the incidence rates over time and by entering time-dependent variables into the model.

This statistic measures model performance by plotting the sensitivity values – the true positive fraction of test points – against 1-specificity – the false-positive fraction for all available probability thresholds [53].