Strategies to maximize generalization from multiple case studies: Lessons from the Africa Routine Immunization System Essentials (ARISE) project

Abstract

This article considers the challenges of generalizability related to case studies, and specifically for the in-depth case studies of the Africa Routine Immunization System Essentials (ARISE) project. The article describes how these challenges were addressed, by developing a Theory of Change to frame case selection strategies, data collection, and analysis, including synthesis of findings across multiple cases. The authors then consider: the importance of grounding generalizability in theory; balancing within-and cross-case analyses for synthesis; and using theory-based case selection, as ways to support generalizability of the case study findings. Multiple case studies should sequence analysis as: 1) within-case analysis; 2) identification of replicated findings and implementation variation across cases; and 3) synthesis across cases, pooling the data. Case selection should be a stand-alone, formative part of case study research. The lessons from the ARISE case studies suggest that these are important ways in which case study methodology can be strengthened.