Multiple descriptor sets are designed for studies using multiple levels of analysis. For example, if a study is comparing the success of different school districts, there might be three levels of data:
1) the district,
2) the schools within a district, and
3) the students within a school.
It is likely that different sets of descriptor variables would be collected at each level, i.e., district level variables (e.g., average family annual income, square miles of capture area, percent rural versus urban neighborhoods), school level variables (e.g., size of student population, student-teacher ratio, percent of children on free lunch program), and student level variables (e.g., age, gender, size of family, language spoken at home, standardized test scores). If the study involves interviews with parents about the home environment, each interview could be linked to three descriptors: the one specific to their child, their child's school, and their school district. Dedoose allows exploration of qualitative data and tagging activity across descriptors. Thus, in a study like this, variation in the qualitative data could be explored as a function of district, school, or student variables or any combination of them.