Participant Variables and Groups

Tobii Pro Lab Tobii Pro Studio

Learn more about how to define independent variables and create participant groups for filtering data in Tobii Pro Lab and Tobii Pro Studio.

Participant variables can be operationalized as the differing individual characteristics that may impact how a participant responds in an experiment. Examples of participant variables include: gender, age, ethnicity, socioeconomic status, literacy status, mood, or clinical diagnosis.  

Participant variables are often considered extraneous variables because they can influence the results of an experiment, even though they are not the focus of your study. Consequently, they need to be controlled for correctly to study or minimize their effects on the experiment.

In this article you will learn how to define participant variables in the Tobii Pro software, Pro Lab and Pro Studio, for data collection, analysis, and interpretation.

Participant variables in Pro Lab

In Pro Lab, you can use the participant variables feature to add participant characteristic information to your project. This enables you to:

  • explore the influence of multiple individual characteristics on eye tracking metrics through statistical tests such as multivariate analysis.
  • statistically control for the potential influence of individual characteristics on the dependent variable(s) to ensure the validity of the experiment’s results
  • to segment your participants into groups to examine whether gaze behavior differs by group status (e.g. clinical vs. non-clinical group).

As long as your participant variable can be characterized into discrete categories, it can be used for further analysis and interpretation in Pro Lab. For example, you can discretize the continuous variable Age into AgeRange with values 18-23, 24-29, 30-34.

Watch a tutorial

Learn how to create participant variables in Pro Lab by watching the video above or by following the instructions below.

Participant variables

Try out using participant variables in Pro Lab for wearable projects

Participant variables

To create you Participant Variables in Pro Lab for wearable-based projects, open the Tobii Pro Lab sample project- Wearable study. Let’s again suppose that we are interested in whether males compared to females show different visual strategies when selecting a hair product and age affects the choice of brand. Therefore, we again end up with two participant variables of interest: Age (<20, 20-29, 30-39,40-49 and >50) and Gender (Male vs. Female).

To create these variables:

  1. Click on the Variables icon on the left of your screen.
  2. In the right pane, click the + button to add variables and values in the same manner as for screen-based projects.
  3. A window will expand to allow you to enter your participant variables. In this example, we will show you how to create the variable Gender.  
  4. Click the + New button on the top right.
  5. Type your Participant Variable of interest (e.g. Gender) into the selection labeled Variable 1.
  6. Click Add new value + to initiate a drop down selection (or hit the enter key to add an additional value).
  7. Type value for Participant variable—in this example, Female.
  8. Click Add new value + to initiate another drop down selection (or hit the enter key to add additional values).
  9. Type second value for Participant variable—in this example, Male.
  10. Repeat the same steps to create the variable Age.

 

Note: If you want to allow the selection of multiple values under a participant variable, check the selection Allow Multi selection.

In this example, we now have two participant variables, Gender (Female, Male) and Age (<20, 20-29, 30-39,40-49 and >50) ready to be assigned to your participants in Pro Lab. To assign each participant their specific characteristics, click on the Participants icon on the left. A Participants panel will now appear on the far right, click on the participant to view the variables available in the project, and select the values in the drop down list.

Participant variables can also be entered or modified after the participant has concluded the study and additional participant variables can be entered at any time. To edit an already completed participant and add participant variable values:

  1. Find that participant in the Participant panel.
  2. Then, click on the participant. On the variable you wish to modify, choose the new value from the drop down list.

Once you have your participant variables defined, you can use them to examine how your gaze data differs along individual characteristics. We can now use the variables we created (Age and Gender) as sorting or grouping variables in the Visualization, Metrics, and Data Export tab of Pro Lab.

 

Visualization

 

To make a heat map of gaze behavior for a "young shopper" group, open the Visualization tab under Analyze. Under Participant Data, check <20 and 20-29. This will display the heat map for "young shoppers" only. If you were to select "young shoppers" and Female, a heat map would display only participants who were female and "young". 

Note: Among the values created for a variable an additional value “not specified” is automatically generated when the project contains participants that were not assigned a value. 

 

Metrics

 

This selection of participants works similarly in the Metrics tab. If you select only "young shoppers" (i.e. Ages <20 and from 20-29), you will be given selected metrics for "young" individuals. If you were to select Major "young shoppers" and Female, you would be given selected metrics for females with ages <20 and between 20-29. Importantly, when you export these metrics for further analysis, it is important to save your files with participant variable selection information in the filename. For example, if you export metrics for females only, a possible name might be DataMetrics_FemalesOnly. If you export metrics for "young" females, the filename might be DataMetrics_Females_Young.

Note: Among the values created for a variable an additional value “not specified” is automatically generated when the project contains participants that were not assigned a value. 

 

Data Export

 

Lastly, gaze behavior can be exported from Pro Lab to other software programs for further analysis in the Data Export tab. To ensure your participant variable data is exported along with the gaze data, ensure the Participant variables column is selected under Metadata columns.

 

 

Participant variables in Pro Studio

Tobii Studio screenshot

Tobii Pro Studio provides a very useful capability for organizing study participants and as an aid for carrying out analyses on subgroups of participants. These two related functions are Independent Variables and Participant Groups.

Independent Variables (IV) can be thought of in the orthodox sense of an experimental condition that is manipulated. It can also be considered, more generally, as a sorting variable. Examples of IVs could be sex, age range, dominant hand, geographic location, income level, or literacy status. As long as the dimension can be listed as discrete categories, you can input them as IVs. This is covered in the Pro Studio manual section 4.2.2. Create your entries by selecting the Independent Variables item under the Tools menu. In the following example, an IV is created for age of the subject, AgeRange, with the possible values of 18-23, 24-29, and 30-34. LowLiteracy is set up to capture subjects’ low literacy status and is dichotomized as Yes or No. Finally, Male and Female are entered as options for the IV Sex.

While IVs can be created here and entered either before or after the subject has actually been tested, there is another way to create and populate IV data. When you include a questionnaire element in the study timeline, each questionnaire item spawns an IV and each response populates the value field with the selected response option (Pro Studio manual section 4.1.2.8). Thus, if a subject is asked to choose their favorite gaming console from the options WiiU, XBOX, or PS4, clicking on the associated radio button will record that value for them in the IV named GameConsole.

However you do it, the creation of Independent Variables sets you up to make use of the Participant Groups (PG) functionality (section 7.2.1). In essence, PGs allow the analyst to slice and dice the total pool of study subjects into subgroups to create comparisons and contrasts when viewing gaze data visualizations or calculating metrics. Let’s see how this works. In the following screen shot, I’ve created nine subjects and populated their IVs. You can see that we have subjects with all possible combinations of the three IVs that we previously created. Now we’re ready to create some participant groups. Note: The values for the independent variables can be edited at any time, which is a helpful capability, especially in the case that a subject makes an unintended or incorrect selection on a questionnaire item.

Tobii Studio screenshot

You can create participant groups in the Visualizations or Statistics tabs in Pro Studio. Since the operation is identical in both places, let’s do it in the Statistics tab for this example. In the next screenshot, I’ve clicked on the Participant Group drop-down. Since we haven’t created any yet, the default option “All Participants” is selected. When you click on “Create new participant group” you are then presented with a popup window where you can select one or more response options for each of the IVs to create a profile for the group.

Conclusion

Participant variables in Pro Lab and Independent variables in Pro Studio, are critical functions that enable you to explore your data with respect to individual (and group) characteristics, i.e. you are able to examine whether gaze behavior differs as a result of specific participant characteristics like age, gender, or group status.

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