Comparing multiple subject groups

#1
Hi all!

I have a question regarding the analysis of some of my dissertation data. Briefly, I have data for a number of biomechanical variables (continuous data -- velocity, angle measurements, distances) for a number of human subjects and two ape subjects performing the same activity. The human subjects are divided into three classes based on their level of experience with the activity. Basically, I am trying to determine:

(1) the differences among the three human groups;
(2) the difference between the apes and humans as a whole; and
(3) the difference between the apes and each human group (i.e., are they more like the least experienced group?).

For humans, I will be analyzing one trial per subject; for the apes, I have available several trials apiece.

The humans-only portion of the analysis is fairly straightforward; I have used one-way ANOVA tests with experience level as the independent factor, followed by Bonferroni post-hoc tests to find the intergroup differences driving the overall ANOVA results. No problem.

However, the ape data are more problematic. I originally included them (separately; they cannot be combined because one is male and one is female, and for biomechanical studies of this type, male and female subjects must be kept separate) as additional levels of the experience variable, but of course this was problematic because it basically compared the means derived from numerous human subjects with means derived from multiple trials of the same ape subject, which are not really analogous measures. There is no way around this subject sample size problem, because there are only two apes who perform the activity under study.

Does anyone have any ideas for how each of the ape subjects might be compared to the humans (both overall and each experience group)?

Thanks so much!