I have 4 groups that are not normally distributed. I would like to know if they are significantly different, with the aim of knowing if they would make a good feature to base a classification on.
I've made box&whisker plots and by looking at them, just by intuition, I feel that they are similar, statistically. That is not very satisfying though and probably not a good way to pass judgment, so I want a way to quantify this. I have been using the Kruskal Wallis test on the groups. Because of the unbalanced group sizes, I don't trust the results. The size of the samples is: 4756, 4018, 1116 and 171. I'm currently getting a p-value of 0.000104, and an H of 21.02
Is there a rule of thumb to follow to know when it is appropriate to test groups with different sizes? I really feel it is unfair to compare a group of 171 to 4756 - that this imbalance should make the comparison invalid. Is the 'solution' to simply say there is not enough data to make a comparison, and wait till more is taken? At what point then would there be 'enough' data or the point when the groups are similar enough size?