As described in INTERACT essentials, INTERACT offers hierarchical elements to structure your observations: DataGroup and DataSet.
Typically, each situation or session is stored within a DataSet.
Once you have more than one DataSet in your data-file, identification of its content becomes more and more important.
Proper identification provides easier to read statistics and simplifies data selection during analysis.
Note: Before you restructure your file(s) or merge data-files, make sure you can identify the content of each DataSet WITHOUT the original file name.
Description line
The simplest method of identification, is descriptive information in the Description line:
▪Click in description field of the Set or Group line you want to edit.
▪Press RETURN to activate the editing mode.
▪Enter the description that identifies the session within.
▪Press RETURN again to confirm your entry.
IMPORTANT: Enter this information before merging multiple data-files!
Make sure the data can be identified without the original filename.
| TIP: | The routine Copy DataGroup description into DataSet description can be found in Additional - Extensions - Functions  < Special data manipulations. |
Independent Variables
For larger studies, with many DataSets per document, identification through the description line alone becomes insufficient. Especially if you need to select specific DataSets during Analysis in various combinations (e.g. all males versus all females or split by age, nationality or any of the other characteristics per participant):
oYou can define as many independent variables as you need.
oYou need to assign the appropriate values for each independent variable per DataSet.
oIt is possible to predefine value lists to choose from, as described in Define Independent Variables.
oIndependent Variables and their values are listed in the Full statistics report.
oYou can limit your selection with the help of independent variables for all DataSet based statistics as well as all Class based statistics.
oIt is also possible to make a raw data selection, based on the available independent variables.