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Defining a data set

Data set structure

The data set structure contains for each subject measurements, dose regimen, covariates etc … i.e. all collected information. The data must be in the long format, i.e each line corresponds to one individual and one time point. Different type of information (dose, observation, covariate, etc) are recorded in different columns, which must be tagged with a column type (see below). The column types are very similar and compatible with the structure used by the Nonmem software (the differences are listed here). This is specified when the user defines each column type in the data set as in the following picture.

Notice that Monolix often provides an initial guess of the type of the column depending on the name.
In addition, we have a button DATA VIEWER that allows to explore the data set as Datxplore.

Description of column-types

The first line of the data set must be a header line, defining the names of the columns. The columns names are completely free. In the MonolixSuite applications, when defining the data, the user will be asked to assign each column to a column-type (see here for an example of this step). The column type will indicate to the application how to interpret the information in that column. The available column types are given below:

Column-types used for all types of lines:

Column-types used for response-lines:

Column-types used for dose-lines:



The name proposed in the figure and in the data choice is the one defined in the label. The user can modify it. By default, the label used is the one defined in the data set.


Loading a new data set

To load a new data set, you have to go to “Browse” your data set (green frame), tag all the columns (blue frame), and click on the button ACCEPT (purple frame) as on the following.


Observation type

There are three types of observations

  • continuous: The observation is continuous with respect to time. For example, a concentration is a continuous observation.
  • discrete: The observation values takes place in a finite categorical space. For example, the observation can be a categorical observation (an effect can be observed as low, medium, high) or a count observation over a defined time (the number of epileptic crisis in a defined time).
  • event: The observation is an event, for example the occurring of an epileptic crisis.

The type of observations can be specified by the user in the interface.