Follow the steps to sort and organize your log files into appropriate folder structure.
By doing so, the outputting .csv files will allow variables indicating main and sub conditions.
Step 1: Download/extract all logs into 1 single data folder.
Step 2: Delete all non-study subject logs (e.g. tester/RA logs in screenshot, etc.) from the single data folder.
Move and store incomplete data of subjects (if you don't plan to use) to a separate folder outside the single data folder.
* If there is no more than 1 session/condition/group/etc. in the study design, you don't have to continue the remaining steps.
Step 3: Create sub folders inside the single data folder based on sessions/conditions/groups/etc.
You may have sub folders inside sub folders. However, only two layers of sub folders is allowed currently.
Sub folder is not required to have if it is not a part of the study design or you simply don't need it.
First layer of sub folders will be outputted as "MainCondition" in the .csv files.
Second layer of sub folders will be outputted as "SubCondition" in the .csv files.
*For Windows users, please avoid whitespaces in your folder names.
Step 4: Filter through all subjects' logs and put them into the sub folders belonged to the subjects.
Refer to the below use cases to find an example.
It is flexible to combine any or all use cases to serve your needs.
Use Case 1: There are more than 1 session in the study battery
*If a session crashed or resumed, extra logs will be created and session numbers in filenames could be different from the actual session.
*Organizing by sessions help with later processing/cleaning/analysis if want to compare across sessions.
*If your situation falls into this use case, please do not use the "SessionNumber" column in the outputting .csv files.
In example screenshoot, 2 first layer sub folders are created under the single data folder "Raw Data."
You can filter and sort log files into corresponding "Session #" sub folders by looking timestamps in log filenames.
*Make sure the "Incomplete Data" folder is outside of the single data folder if you don't plan to use them
*You should use the path/directory of "Raw Data" folder when running the scripts
Use Case 2: There are more than 1 condition in the experiment design
In example screenshoot, experiment has 2 conditions - subjects are randomly assigned to different interventions.
2 first layer sub folders are created under the single data folder "Raw Data" indicating 2 interventions.
You can filter and sort log files in to corresponding "[Intervention]" by matching your record.
In addition, 2 second layer sub folders are created under the first layer sub folders.
You can filter and sort log files into corresponding "Session #" sub folders by looking timestamps in log filenames.
*Make sure the "Incomplete Data" folder is outside of the single data folder if you don't plan to use them
*You should use the path/directory of "Raw Data" folder when running the scripts
Use Case 3: There are more than 1 group because of subject characteristics
In example screenshoot, study recruits subjects who have different levels of language skills - monolingual/multilingual.
2 first layer sub folders are created under the single data folder "Raw Data" indicating 2 levels.
You can filter and sort log files in to corresponding "[Levels]" by matching your record.
In addition, 2 second layer sub folders are created under the first layer sub folders.
You can filter and sort log files into corresponding "[Pre/Post]" sub folders by looking timestamps in log filenames.
*Make sure the "Incomplete Data" folder is outside of the single data folder if you don't plan to use them
*You should use the path/directory of "Raw Data" folder when running the scripts