Amount of rejected data
Hi all,
I have been advised to include an overview of how much pupil size data I had to reject per participant, that was labeled as outlier (biologically invalid samples, blinks, samples with high dilation speed, etc.).
Do you have an example in mind, of a paper where they have done such a thing? or do you have a measure for doing this?
If I want to go in details, I seem to have to repeat all my preprocessing steps and somehow make a note of how many samples are being rejected or interpolated or somehow compensated for.
Thanks in advance!
Zahra
Comments
Hi Zahra,
Do you have an example in mind, of a paper where they have done such a thing? or do you have a measure for doing this?
There is no standard way of reporting this. In this article, we provide some guidelines for pupil-size preprocessing and indirectly also for how to report this. However, it sounds like you're using a quite different preprocessing pipeline from ours. That's not a problem at all, because there are multiple reasonable approaches to pupil-size preprocessing. But it does mean that you'll have to think of your own ways to report this.
If I want to go in details, I seem to have to repeat all my preprocessing steps and somehow make a note of how many samples are being rejected or interpolated or somehow compensated for.
Yes. It's good practice to do that in any case, because it will give you some idea of the quality of your data and where potential issues are. For example, if you notice that lots of samples are excluded based on blinks, then this might suggest that the display was too bright, causing participants to blink a lot. (This is just a random example; the main point is that it's good to understand your data.) Visualizing your data is also important in this regard!
My overall recommendation would be to visualize your data, get an understanding of how much data you lose because of which criteria, and then use common sense to report those things that are meaningful to the reader. The paper that I linked to above is intended to illustrate one way to do this.
— Sebastiaan
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Thanks a lot @sebastiaan this was helpful!