Q Squared: Combined Qualitative & Quantitative

By using data from a variety of sources and qualitative and quantitative methods, it is possible to cover a wide range of issues and topics relatively efficiently. Rather than seeing this as a second-best solution, such a combined approach can actually provide a more convincing analysis than any single method. This is because studies have found that people respond differently to quantitative and qualitative information. Numbers are required to convince some audiences, while others will be unimpressed by numbers, but relate more to in-depth and contextual information gathered using qualitative techniques.  Triangulation, where several types of data are used in a single study, and used to cross-check and compare results, enables any weaknesses in one method to be offset by the strengths of another.

An assessment of 57 mixed method studies identified five purposes for mixing methods: (1) triangulation—seeking convergence of results; (2) complementarities—examining overlapping and different facets of a phenomenon; (3) initiation—discovering paradoxes, contradictions, fresh perspectives; (4) development—using the methods sequentially, such that results from the first method inform the use of the second method; and (5) expansion—adding breadth and scope to a project.[1]

For more detailed information about Q squared methods for impact evaluation and for monitoring and evaluation see the Methods section of the Gender and Assets Toolkit.

[1] Greene, Caracelli, and Graham (1989), cited in Adato (2007).