Case selection for robust generalisation: lessons from QuIP impact evaluation studies

What wider lessons can be drawn from a single impact evaluation study? This article examines how case study and source selection contribute to useful generalisation. Practical suggestions for making these decisions are drawn from a set of qualitative impact studies. Generalising about impact is a deliberative process of building, testing and refining useful theories about how change happens. To serve this goal, purposive selection can support more credible generalisation than random selection by systematically and transparently drawing upon prior knowledge of variation in actions, contexts, and outcomes to test theory against diverse, deviant and anomalous cases.