Hi everyone,
In my experiment I am presenting 200 participants with a subset of 50 unique images from a larger set of 191 images (participants will view the image, type the name of image in a textbox and also rate it across a few rating scales). The subset of images presented will be randomised for each participant.
To do this, I have set up my experiment using the method that seems to be most commonly recommended i.e., put all 191 images in the one csv file, set the experiment up as though all 191 will be randomly presented (using Psychopys randomisation feature), but then insert code in the end routine tab to end the routine after 50 trials (e.g., see here: How to present subset of all images randomly)
However, I wanted to ask if this method creates any risk that across my 200 participants, there will be considerable variation in how many times each image has been viewed e.g., some appear for almost every participant, whereas others are only seen by a few participants. My feeling is that this is really unlikely, since (I think) there is around a 1 in 4 chance of each image been shown for any given participant (and I’ll have a sample of 200 participants). However, I am not an expert in Psychopys randomisation feature, and it is possible I am overlooking something here.
I would be grateful if anyone could give advice on this.
Thank you!