Mixed methods are the explicit adoption of both quantitative and qualitative methods in the impact evaluation design (White, 2008).

The debate around ‘mixed methods’, also known as ‘Q-squared in Policy’ has stressed the complementarities of the two approaches. That is the depth from qualitative research and the statistical robustness from quantitative research often inform, correct and augment each other (Shaffer et al, 2009).  Important aspects of this complementarity are that mixed methods for impact evaluation ensure that the research process  is used as a way of increasing accountability and empowerment of the poor (Garbarino and Holland, 2009), and that participatory research offers qualitative insights and generates statistics for relevant dimensions that might otherwise be overlooked (Chambers, 2007).