Mixed methods research stems from the idea that various methods share a "unified framework." Such a notion came as pushback to the methodological debates which often left a wide gap between qualitative and quantitative research, making knowledge accumulation as an overarching objective difficult to achieve. Mixed methods research is an answer to this gap, because it is well-suited to triangulating data, answering "big" questions, and elucidating more clearly the various components of a causal chain. This chapter will provide an overview of the do's and don't's of mixed methods research, by outlining the different forms such research can take, as well as the benefits and challenges of this kind of research design. It will also include examples of how mixed methods research can be applied to IR, and provide resources for those new to the method.
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