The figure displays the individual parameters as a function of the covariates. It allows to identify correlation effects between the individual parameters and the covariates.
Identifying correlation effects
In the example below, we can see the parameters Cl_obs and Cmax with respect to the covariates: the weight WT, the age AGE and the sex category.
In order to help identifying correlations, regression lines, spline interpolations and correlation coefficients can be overlaid on the plots for continuous covariates. Here we can see a strong correlation between the parameter Cl_obs and the age and the weight.
Overlay of values on top of the boxplot
The NCA parameter values used to generate the boxplots for the categorical covariates can be overlayed on top of the boxplots, which enables to better visualize the distribution in case of a small number of individuals.
Hovering on a point reveals the corresponding individual and, if multiple individual parameters have been simulated from the conditional distribution for each individual, highlights all the points points from the same individual. This is useful to identify possible outliers and subsequently check their behavior in the observed data.
It is possible to select a subset of covariates or parameters, as shown below. In the selection panel, tick the items you would like to see and click “Accept”. This is useful when there are many parameters or covariates.
Stratification can be applied by creating groups of covariate values. As can be seen below, these groups can then be split, colored or filtered, allowing to check the effect of the covariate on the correlation between two parameters. The correlation coefficient is updated according to the split or filtering.
- Legend: add/remove the legend. There is only one legend for all plots.
- Grid: add/remove the grid.
- Information: display/hide the correlation coefficient associated with each scatter plot.
- Units: display/hide the units of the NCA parameters on the y axis
- Individual parameters: Selects the NCA parameters to display as subplot on rows. Tick the items you would like to see and click “accept”.
- Covariates: Selects the NCA parameters to display as subplot on columns. Tick the items you would like to see and click “accept”.
- Boxplots data: overlay the NCA parameters as dots on top of the boxplots for categorical covariates, either aligned on a vertical line (“aligned”), spread over the boxplot width (“spread”) or not at all (“none”).
- Regression line: Add/remove the linear regression line corresponding to the correlation coefficient.
- Spline: Add/remove the spline. Spline settings cannot be changed.