Use when designing or conducting case study research following Yin's multiple case study methodology or Stake's approach.
A case study examines a bounded system (a case) using multiple sources of evidence. It is suited to “how” and “why” questions where the researcher has little control over events, and context matters. Robert Yin and Robert Stake offer influential, partially complementary frameworks.
Yin emphasizes rigor through design, not just data collection. A case is an empirical unit (e.g., organization, program, community, event) analyzed in depth.
Cases should align with research questions and propositions (if used). For multiple cases, define selection criteria before data collection when possible to reduce cherry-picking. Document why cases were included or excluded.
Optional but powerful: explicit expectations guide data collection priorities and analytic focus (e.g., “Implementation success depends on leadership support”). Propositions differ from hypotheses in quant studies—they orient inquiry while allowing qualitative refinement.
Typical sources:
Yin stresses converging evidence (triangulation) and a case study database (organized raw data, logs, and analysis notes) separate from the final report.
Readers should be able to trace claims → displays → data. Maintain:
For each case, produce a standalone description and within-case analysis. Then conduct cross-case comparison using a uniform framework (e.g., tables of constructs). Look for patterns, contrasts, and theoretical replication support.
The case itself is of primary interest (e.g., a particular school). Findings emphasize understanding that case, not broad laws.
The case is examined to illuminate a broader issue or refine a theory. The case remains particular, but the lens is instrumental to external understanding.
Several instrumental cases shed light on a phenomenon; resonates with Yin’s multiple-case design but retains Stake’s emphasis on experience and interpretation.
| Feature | Yin | Stake |
|---|---|---|
| Emphasis | Design, replication, propositions | Interpretation, portrayal, experience |
| Generalization | Analytic generalization to theory | Naturalistic, reader-led |
| Rigor | Database, chain of evidence, methods triangulation | Interpretive discipline, reflexivity |
Use this skill when the user designs multi-site evaluations, organizational studies, or compares Yin and Stake for dissertation methodology.