What statistics can compare individual survey responses & others that were measured as a group (from which we need to extract individual responses)? The organization I belong to studies indigenous populations through primarily survey research. One study for example aims to identify the relationship between culture and the evaluation of odors. We are looking for a statistical procedure that can be used to compare a larger amount of individuals. Some records were measured directly on individuals, while others were measured by a group spokesman. In the case of groups, however, individuals should be "downscaled" in order to be able to compare these data records with the data sets of individuals measured. The group speakers of a group are not always the same people from a particular group, but different people can respond on behalf of the group. The group size can vary within the measurement. A mean number of group size, ratio between man and woman and age is estimated per questionnaire/measurement (data set). Due to the difficulties collecting data in indigenous contexts, this is the only way we found to be possible. We are looking for a statistical method that can compare individual survey responses, if some were measured individually, and others were measured as a group (from which we need to extract individual responses).
Sounds like you're looking for a hierarchical model. You might find some joy in  BDA, http://www.stat.columbia.edu/~gelman/book/ (in particular, chapter 5)

To quickly get some idea if this sort of thing is right for you, you could check out this blog-post on one particular example here http://andrewgelman.com/2014/01/21/everything-need-know-bayesian-statistics-learned-eight-schools/

Whether this will work for you also depends quite a bit on what you want to ask (what does 'identify the relationship' mean?) and the target audience. If you do head over to Cross Validated (strongly recommended!) make those things as clear as possible in your question.