This compatibility check allows you to determine whether or not the imported data is compatible with the populations defined in the library.
App Admins can create populations in the library settings to help streamline sampling and to standardize the data their teams see within MindBridge. However, certain populations set up in the library may contain conditions that are not compatible with the imported dataset — this could be due to missing data fields in the imported file or unmapped columns.
Learn how to access and run a compatibility check on your imported data.
Access populations within the import checklist
- Select the logo in the MindBridge sidebar.
You will go to the Organizations page.
- Select View in line with the desired organization, or click anywhere in the organization row.
You will go to the Engagements page.
- Select View in line with the desired engagement, or click anywhere in the engagement row.
You will go to the Data page for that particular engagement.
- Open the more actions menu ( ) in line with the desired analysis name.
- Select View checklist.
The import checklist will appear.
- Select the chevron icon ( ) beside Populations to expand the section.
You will see the option to run a compatibility check
Tip: If you are already in an engagement, open the sidebar ( ) and select Data ( ), then skip to step 4 in the instructions above.
Run the compatibility check
Select Run compatibility check within the Populations section.
MindBridge will begin going through the data to ensure the populations are compatible with your analysis data. If MindBridge detects data missing from the imported files, you will see a list of the missing fields within the import checklist.
Re-run the compatibility check
If you want to re-import files or update your column mapping, you may do so before running the analysis. You will have the opportunity to re-run the compatibility check against the new data.
Select Re-run compatibility check within the Populations section to run the check again.