Comparative Qualitative Research Methods Oxford University, Hilary Term 2006 Wk 7: Single Case Analysis

1. Comparative Qualitative Research MethodsOxford University, Hilary Term 2006Wk 7: Single Case Analysis Adrienne LeBas Nuffield College, Oxford Email: adrienne.lebas@nuffield.ox.ac.uk Phone: 01865 278518

2. Case Studies and Qualitative Methods

3. Case Selection (cont�d): Cautions about KKV Historically, in small-N qualitative research: Selection on DV is common � self-conscious selection of cases? Research designs based on �extreme values� of particular variables often useful � why not non-revolutions? How to choose the right non-cases? Attempts to boost N may lead to other problems, poor estimation of causal effects � comparability of cases!! Using full universe of cases imposes heavy burden for data collection, especially if question is new or understudied � can collaborative research add up to a whole?

4. Selection on the DV Is random selection of cases analytically defensible? Alternative strategies for case selection. All variable values must not be represented to get covariation. Counterfactuals can be used. Extreme Values: Research designs choose extreme values of phenomena that are intuitively of interest (e.g., revolution) or research designs assume that some subset of cases with extreme values operate differently from the broader universe of cases (e.g., East Asian tigers)

5. Selecting Cases and Small-N Research Designs If you do accept similar causal inference in small and large-N analysis: Explicitly justify selection of cases. Cases must represent full range of variation on DV. If your theory has X variables that are assumed to have a causal effect, you should have X+1 (or more) observations. If in doubt, increase N. Can be done within case (time, space). If N cannot be increased, minimize some of the variation across cases.

6. Selecting Cases and Small-N Research Designs If you don�t accept similar causal inference in small and large-N analysis: Explicitly justify selection of cases. Establish comparability of cases; discuss the work that individual cases will do. Demonstrate consistency in conceptualization / measurement of variables across cases. No rule re: number of cases / observations. If in doubt, increase leverage of causal hypotheses via within-case analysis.

7. The Case of Skocpol: What do Individual Cases do in CHA? Comparative Historical Analysis: Use of comparison of small number of cases to shed light on macro-historical phenomena (Skocpol; B. Moore; Luebbert; A. Marx; G. Capoccia) Assumption that comparison is driving causal inference: use of Millean methods (see Geddes critique of Skocpol) Suspiciously, however, CHA is usually organized in case study format

8. Cases as Data Points? KKV / Lijphart approach: Individual cases as agglomerations of variables. Task is to �code� values of each variable, then use comparison to establish causal effects. True case study approach: Individual cases as both wholes and instances of general phenomenon. Task is to establish relationships between variables.

9. The Single Case Study Gerring 2004: �an intensive study of a single unit for the purpose of understanding a larger class of (similar) units� (342) Covariation does not require multiple units, as causes and effects change within a single unit (over time or over space) No requirement of comparison across units to establish covariation, causal relationship

11. Advantages of Small-N and Single Case Analysis Identification of causal mechanisms Unit homogeneity: cases are comparable Conceptual clarity: interplay between conceptualization and categorization Less susceptible to omitted variables Can cope with causal complexity

12. What Case Studies Do Research tasks other than causal inference: Concept formation; operationalizatn of variables. Hypothesis generation: case studies as exploratory research. Heuristics: Identification of causal mechanisms that may be generalizable to larger universe. Confirmation / Disconfirmation: Crucial cases. Stronger where causality not probabilistic.

13. Types of Case Studies(Eckstein 1975) Configurative-idiographic: Gerring would not define this as a case Disciplined-configurative: case as test of existing theory Heuristic: case provides building blocks of theory Plausibility probe: may establish scope of theory Crucial case: test of theory

14. �Most likely� and �least likely� research designs Crucial case studies: case study as experiment (Eckstein 1975: 116) Criticism #1: How does one identify crucial cases? Prior comparison necessary. �Folk Bayesian� approach: crucial cases don�t operate in a vacuum Criticism #1: only have value if they are �deviant cases;� can only disconfirm or modify established generalizations from elsewhere Causal mechanisms approach; reliability of observations may be high

15. Intra-Case Complexity Intensive study of single cases can also deal with complex processes that are often ignored in quantitative research �Hidden� processes: Scott and �weapons of the weak�; contextual interpretation Time: critical junctures; path dependence Concatenations of mechanisms � We�ll discuss ways of dealing with these issues next week!!