The aim of this app is to allow you to visualise the effects of preprocessing choices on means and SDs for individual conditions for individual participants.

Initially, the app expects you to click on “Browse” to upload a PsychoPy outfile in .csv format. You are then asked to provide the app with the following information:

• The name of the main loop in the Flow: This will be used to identify your experimental trials (and to reject all other trials that might be part of the experiment).
• The column with RT data: The RTs are what will be plotted, thus the app needs to know the column in which it can find the RTs.
• The column that includes the condition: The app assumes that you will plot one individual condition from the experiment and that there is one column that can be used to identify this condition. Select this column here. E.g., the relevant column might be called congruency.
• The condition: Once you have selected the column, you can select the condition. E.g., the condition might be incon.

Note that you can type in the dropdown fields. E.g., if you type .rt, you will only see columns that contain .rt in the header.

Once you have made these choices, the app will plot the data on the tab “Visualisation”. On the left side of the plot, you will see a plot of every data point for the specific condition you selected. Next to this (labelled “Before”), you will see a visualisation of the mean and SD without any preprocessing applied to the data. On the right (labelled “After”), you will see a visualisation of the mean and SD after preprocessing steps have been applied to the data. Initially, “Before” and “After” will be identical. “After” will be updated when you select preprocessing steps. The exact mean and SD can be found below the plot.

Note that the preprocessing choices can be applied individually or in combinations. This is how these choices will be visualised:

• Remove extreme trials: After entering numbers for the lower and upper thresholds, solid lines will indicate the location of these thresholds on the left-most plot. Any data points outside these lines will be removed for calculating the “After” mean and SD.
• Remove incorrect trials: The colour of the dots will change. A legend on the right will indicate the colours for correct (labelled 1) and incorrect trials (labelled 0). All incorrect trials will be removed for calculating the “After” mean and SD.
• Remove outlier trials: After entering a multiplier for the SD, dashed lines will indicate the location of the thresholds on the left-most plot. Any data points outside these lines will be removed for calculating the “After” mean and SD.

Note that if outlier trial removal is combined with another preprocessing choice, outlier removal is always performed last. E.g., if incorrect trial removal and outlier removal are combined, the calculation of the SD for outlier removal is based on only correct trials.