| name | case-study-methods |
| description | Use when designing or conducting case study research following Yin's multiple case study methodology or Stake's approach. |
Case Study Research Methods
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’s logic of the case study
Yin emphasizes rigor through design, not just data collection. A case is an empirical unit (e.g., organization, program, community, event) analyzed in depth.
Single vs multiple case designs
- Single case — Justified when the case is critical, unique, revelatory, or longitudinal. Risk: weak generalization.
- Multiple case — Replication logic (literal or theoretical): cases are chosen to predict similar results (literal replication) or contrasting results for predictable reasons (theoretical replication). Strengthens analytic generalization to theory, not statistical populations.
Holistic vs embedded
- Holistic — The case as a single unit of analysis.
- Embedded — Subunits (e.g., teams within a firm) analyzed; requires clarity about how subunit findings aggregate to the main case.
Case selection
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.
Theoretical propositions
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.
Data collection in case studies
Typical sources:
- Interviews — Key actors, triangulated roles.
- Documents — Minutes, policies, reports, communications.
- Direct observation — Meetings, workflows, artifacts in use.
- Archival records — Metrics, histories, legal filings.
Yin stresses converging evidence (triangulation) and a case study database (organized raw data, logs, and analysis notes) separate from the final report.
Chain of evidence
Readers should be able to trace claims → displays → data. Maintain:
- Citation to specific sources (interview ID, document type, date).
- Clear protocols linking evidence to assertions.
- Analytic memos documenting interpretive leaps.
Analytic strategies (Yin)
- Pattern matching — Compare empirically based patterns to predicted ones; may involve rival explanations ruled out by evidence.
- Explanation building — Iterative narrative linking causes and outcomes; guard against researcher bias through triangulation and disconfirming evidence.
- Time-series / logic models — When temporal ordering or program theory is central.
Cross-case synthesis (multiple cases)
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.
Stake’s approach: intrinsic vs instrumental
Intrinsic case study
The case itself is of primary interest (e.g., a particular school). Findings emphasize understanding that case, not broad laws.
Instrumental case study
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.
Collective case studies
Several instrumental cases shed light on a phenomenon; resonates with Yin’s multiple-case design but retains Stake’s emphasis on experience and interpretation.
Stake’s emphases
- Thick portrayal of cases and reader naturalistic generalization.
- Attention to emic views and interpretive rigor rather than only deductive propositions.
- Progressive focusing — Early field visits inform what matters next.
Yin vs Stake (practical contrast)
| 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 |
Reporting
- Clear case boundaries and context.
- Methods section with data sources and analysis steps.
- Within-case chapters/sections before cross-case synthesis.
- Explicit limitations and rival interpretations considered.
Use this skill when the user designs multi-site evaluations, organizational studies, or compares Yin and Stake for dissertation methodology.
