Data vizualization


There are several representations depending on the type of data under consideration.

Outcome visualization

The representation of the outcome w.r.t. time is proposed in the Dataviewer frame.

It is possible to play with the axes to have a log-scale display as on the following:

An interesting feature is the possibility to display the dosing times as on the figure below. In the proposed example (PKVK_project of the demos), the individual dosing time of the individual is displayed when the user hovers over an individual’s data.

Informations are also provided with:

  • The total number of subjects
  • The average number of doses per subject
  • The total, average, minimum and maximum number of observations per individual.

In addition, if we split the graphic based on a covariate, the informations adapt to the subplots:

In case of several continuous outputs, one can plot one outcome w.r.t. another one as on the following figure for the warfarin data set. The direction of time is indicated by the red arrow.

For discrete outcomes, it is possible to display the outcome both as continuous outcomes or stacked as on the following figure corresponding to the Zylkene data set.

For time-to-event data, one can see the empirical Kaplan-Meier plot of the first event as on the following example of the length of hospital stay for cardiovascular patients.

Covariate display

It is possible to display one covariate vs another one. In the following figure, we display the age versus the wt and show the correlation coefficient as an information.

We can also display categorical covariates w.r.t. an another categorical covariate as an histogram (stacked or grouped), 

and a continuous covariate w.r.t. a categorical covariate as a boxplot as on the following example.

modal close image