Strategies to integrative mixed methods analysis

Data analysis is the most challenging step in mixed methods research, especially if it is done integratively. Data integration refers to the merging of different data elements to produce a result that is bigger than the sum of its parts. This chapter outlines challenges in analyzing data integratively. I focus on data linkage, transformation, and consolidation as integrative strategies, and I illustrate them with an empirical example. Using this foundation, I problematize the qualitative-quantitative dichotomy and call for more creative and flexible - yet reflected - thinking around integration that goes beyond terminological boundaries to advance methodological as well as substantive research.