I have data from a study in which subjects were listening to a musical piece and asked to press a key at certain moments. The time axis has been segmented into adjacent epochs of time (of varying durations) that have, for music analysis purposes, been labelled as type A, B or C. Adjacent epochs are not necessarily of the same type, and there are more type-B and type-C epochs than there are of type-A.
For each subject, I computed a keypress count within each epoch in the piece, and thus obtained cross-subject means for each epoch, several ones for each epoch type (A,B,C).
I would like to do a statistical test between these group means to check for a significant difference between A-B-C, but the problem I see is there being an unequal number of elements (epochs) in each of the 3 groups. I think a repeated-measures ANOVA is therefore probably unsuitable.
I also think based on this past CV post that the unequal-number-of-elements-in-each-group problem can be overcome by computing pair-wise differences when such pairs can be defined, and then running paired-samples t-test on the difference (A vs B, B vs C, A vs C). However, I am not sure this data is truly "paired" since the data points refer to epochs from various parts of the piece; or even really "repeated measures" in the traditional sense!
Does it even make sense to run a statistical test in this case, and if so, which test is appropriate?