This is not really a coding question but more of a statistical question.
I'm doing a proportions test on multiple proportions for many subjects.
For example, subject 1 will have multiple proportions (multiple "successes per total trials"), and subject 2 will have multiple proportions. And for each subject we're testing if all these proportions are the same. For each subject, there are multiple proportions where there is number of successes per total trials. The proportions could range from being 30 successes out of 60 to like 300 successes out of a 1000 (just to show the range of trials and successes for each subject). Furthermore, for each subject, there could be varying number of proportions. Subject 1 could have 50 proportions, whereas subject 2 could only have 2. The idea is that we're trying to test that for each subject that all of their proportions are the same, and then reject if they are different.
However, I'm realizing that subjects that have many more proportions, will have more significant p-values than subjects that only have 2 proportions, when using the prop.test. I was wondering if there is a way to approach this problem in a different way. Any sort of correction I could do, or take into account the number of positions.
Any suggestions would be helpfil.