Counterbalancing not respecting requested group totals

I could very well imaging that this is what happens, in particular if you use recruitment services (such as Prolific, Testable Minds, etc) who recruit a lot of participants in a very short time, so that you'll have always quite a few participants doing the study at the same time. One reason might be that you need to count the participants who *finished* the study for counterbalancing, because participants may terminate early. And then you might end up with 10 10 10 per group, but with an unequal number of incomplete datasets in each group.

See my thread (https://psytoolkit.boards.net/thread/767/suggestion-counterbalancing) as well, it seems that participants (at least in the beginning?) are assigned randomly to groups. Maybe they are assigned randomly throughout (each new participant has a 33% chance to be assigned to one of the groups) so that the 10 10 10 is only the ideal target but not fully guaranteed?

In the end I didn't use it anymore, but instead created 2 different experiments, using two different links (and creating two studies on Testable Minds. Although I've now found out that one could balance this also in Testable. In other words, writing a very brief 'wrapper' experiment in Testable which just assigns the participants to the two groups in a balanced fashion).

For larger samples or projects where perfect balancing isn't required, I guess it's still a very useful function.