Scholars have created a variety of typologies to describe and simplify mixed methods research designs. In this article, I review the rationale for using these typologies and discuss some shortcomings of the existing methods of classification. I argue that current systems of classification, although useful for simple and less fluid types of mixed methods research, are not capable of capturing the complexity and iterative nature of larger, more intricate research projects. I suggest an alternative way of viewing and describing mixed methods research for studies that resist simple classification. This alternative perspective shifts the unit of reference to the point of interface—where QUAL and QUAN data are integrated—and reduces the number of descriptive dimensions to two—the timing and the purpose of data integration.
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