Description of column-types used to define controls and events

EVID: event identification data item.

EVID corresponds to the identification of an event. It is an integer between 0 and 4. It helps to define the type of line.

  • EVID = 0: observation event, the line is a response-line.
  • EVID = 1: dose event, the line is a dose-line.
  • EVID = 2: other event. UNUSED (exception thrown). To define times for model predictions without corresponding observations, use MDV=2.
  • EVID = 3: reset event. UNUSED (exception thrown).
  • EVID = 4: reset + dose event, indicates a wash-out (i.e reset to initial values) immediately followed by a dose.

Format restrictions (an exception will be thrown otherwise):

  • A data set shall not contain more than one column with column-type EVID.
  • EVID shall contain an integer in [0, 4].
  • when a line is tagged (EVID = 0), the observation contained in column Y shall be convertible to a double value.
  • when a line is tagged (EVID = 1, EVID = 4), the value in dose-column (i.e. content of the column with column-type AMT) shall be convertible to a double.

MDV: missing dependent variable.

The MDV column-type enables to tag lines for which the information in the Y column-type is missing. Most of the time, this column is not necessary.

  • MDV=0: when a line is tagged MDV = 0 AND if it contains a string convertible to a double value in response-column (the column with column-type Y), then the value in the Y column is taken into account. Values in dose-column (the column with column-type AMT) will not be taken into account.
  • MDV=1: when a line is tagged MDV = 1 then the value in column Y will not be taken into account. The value in dose-column, if present, will be taken into account.
  • MDV=2: when a line is tagged MDV = 2 then the value in the response-column is not taken into account. The value in dose-column, if present, will be taken into account. The time, covariates, regressors, etc will be taken into account to output a prediction at that time point.

If there are both a MDV and EVID columns, the EVID column is used in priority.
The MDV column is useful to ignore specific response-lines, for instance if the observation is obviously wrong. If a MDV column is added to the dataset, the response-lines to ignore should have MDV=1, but also the dose-lines should have MDV=1 (otherwise the dose will be ignored). MDV=2 permits to define times at which model predictions should be outputted, even if there is no corresponding observation.When there are multiple MDV columns, a synthetic value MDV is computed as:

  • if MDV = 0 in all columns, then resulting synthetic MDV equals 0.
  • if MDV = 1 in at least one column and the other equals 0, then the resulting synthetic MDV equals 1.
  • if MDV = 2 in at least one column and the other equals 0, then the resulting synthetic MDVsynth equals 2.

 

Format restrictions (an exception will be thrown otherwise):

  • MDV shall contain only integers belonging to interval [0, 2].
  • When MDV=0, the value in the Y column should be convertible to a double value, otherwise an exception will be thrown.