Case Study: Logic

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Case Study: Methods and Analysis whether statistical generalizations offer plausible or spurious explanations of individual cases, the incorporation of equifinality and complex interactions effects, and the inferences made possible by combining within-case and cross-case analyses (Collier 1993, Munck 1998, George and Bennett 2001). It is possible that new statistical methods may be able to improve upon the statistical treatment of equifinality and interaction effects, and at least narrow the gap in the treatment of this issue, but the other comparative advantages of case study methods appear to be inherent in their differences from statistical methods. The limits of case study methods include their inappropriateness for judging the relative frequency or representativeness of cases, their weakness at performing partial correlations and establishing causal effects or causal weight, the necessarily narrow and contingent nature of their generalizations, and the danger that selection bias can be more catastrophic than in statistical studies (Collier 1993, King et al. 1994, Munck 1998, George and Bennett 2001). Fortunately, these are precisely the strengths of statistical studies. 4. Future Directions in Case Study Methods Just as the formalization of case study methods in the 1970s inspired a generation of more sophisticated research, the recent further refinements in these methods are likely to lead to still greater sophistication in their use in the social, biological, and even physical sciences. The increasingly evident complementarity of case study and statistical methods is likely to lead toward more collaborative work by scholars using various methods. The recent interest among rational choice theorists in using case studies to test their theories, for example, is an important step in this direction (Bates et al. 1998). Because case studies, statistical methods, and formal modeling are all increasingly sophisticated, however, it is becoming less likely that a single researcher can be adept at more than one set of methods while also attaining a cuttingedge theoretical and empirical knowledge of their field. Collaboration might therefore take the form of several researchers working together using different methods, or of researchers more self-consciously building on the findings generated by those using different methods. In either form, effective collaboration requires that even as they become expert in one methodological approach, scholars must also becomeconversantwithalternativeapproaches,aware of their strengths and limits, and capable of an informed reading of their substantive results. See also: Biographical Methodology: Psychological Perspectives; Case Study: Logic; Case-oriented Research; Configurational Analysis; Human–Environment Relationship: Comparative Case Studies; Psychotherapy: Case Study; Single-case Experimental Designs in Clinical Settings; Single-subject Designs: Methodology Bibliography Bates R H, Greif A, Rosenthal J, Weingast B, Levi M 1998 Analytic Narraties. Princeton University Press, Princeton, NJ Collier D 1993 The comparative method. In: Finifter A W (ed.) Political Science: the State of the Discipline II. American Political Science Association, Washington, DC Collier D, Mahoney J 1996 Insights and pitfalls: selection bias in qualitative research. World Politics 1: 56–91 Eckstein H 1975 Case studies and theory in political science. In: Greenstein F I, Polsby N W (eds.) Handbook of Political Science. Addison-Wesley, Reading, MA, Vol. 7 George A L 1979a Case studies and theory development. In: Lauren P G (ed.) Diplomacy: New Approaches in Theory, History, and Policy. Free Press, New York George A L 1979b The Causal nexus between cognitive beliefs and decision-making behavior: the ‘Operational Code.’. In: Falkowski L S (ed.) Psychological Models in International Politics. Westview, Boulder, CO George A L, Bennett A O 2001 Case Studies and Theory Deelopment. MIT Press, Cambridge, MA Goldstone J 1997 Methodological issues in comparative macrosociology. Comparatie Social Research 16: 107–20 Goldthorpe J 1997 Current issues in comparative macrosociology. Comparatie Social Research 16: 1–26 King G, Keohane R, Verba S 1994 Designing Social Inquiry. Princeton University Press, Princeton, NJ Lakatos I 1976 Falsification and the growth of scientific research programs. In: Lakatos I, Musgrave A (eds.) Criticism and the Growth of Knowledge. Cambridge University Press, Cambridge, UK Lijphart A 1971 Comparative politics and the comparative method. American Political Science Reiew 65: 682–93 Lijphart A 1975 The comparable cases strategy in comparative research. Comparatie Political Studies 8: 158–77 Little D 1998 Microfoundations, Method, and Causation. Transaction, New Brunswick, NJ Mahoney J 1999 Nominal, ordinal, and narrative appraisal in macro-causal analysis. American Journal of Sociology 104: 1154–96 McKeown T 1999 Case studies and the statistical world view. International Organization. 1: 161–90 MunckGL1998Canonsofresearchdesigninqualitativeanalysis. Studies in Comparatie International Deelopment 33: 18–45 Njolstad O 1990 Learning from history? Case studies and the limits to theory-building. In: Gleditsch N P, Njolstad O (eds.) Arms Races: Technological and Political Dynamics. Sage, Newbury Park, CA Przeworski A, Teune H 1970 The Logic of Comparatie Social Inquiry. Wiley-Interscience, New York Ragin C C 1987 The Comparatie Method: Moing Beyond Qualitatie and Quantitatie Strategies. University of California Press, Berkeley, CA Ragin C C 2000 Fuzzy-Set Social Science. University of Chicago Press, Chicago, IL RaginC C,BeckerH S1992Introduction.In:RaginC C,Becker H S (eds.) What is a Case? Exploring the Foundations of Social Inquiry. Cambridge University Press, Cambridge, UK 1518
Case-oriented Research Rogowski R 1995 The role of theory and anomaly in socialscientific inference. American Political Science Reiew 89: 467–70 Sartori G 1970 Concept misformation in comparative politics. American Political Science Reiew 64: 1033–53 Van Evera S 1997 Guide to Methods for Students of Political Science. Cornell University Press Ithaca, NY Verba S 1967 Some dilemmas in comparative research. World Politics 20: 111–27 Case-oriented Research 1. Introduction A. Bennett Case-oriented research focuses on interconnections among parts and aspects within single cases. In this approach, the researcher attempts to make sense of each case as a singular, interpretable entity. In-depth knowledge of the cases included in a study is considered a prerequisite for the examination of patterns that might be observed across cases. Case-oriented researchers often study one case at a time, but they may also study multiple instances of a given phenomenon (e.g., comparable instances of ethnic conflict). The distinctiveness of case-oriented research is apparent when this approach is contrasted with the variable-oriented approach, where researchers focus more exclusively on cross-case patterns, without first gaining an understanding of each case. 2. Goals of Case-oriented Research Today social scientists tend to identify case-oriented research with specific techniques of data collection linked to the observation and analysis of singular cases (e.g., direct observation of individuals at the micro level and archival research on nation-states at the macro level). While generally useful, the identity of case-oriented research with specific techniques of data collection is unfortunate, for it obscures basic differences between case-oriented research and conventional variable-oriented research. More fundamental than differences in methods of data collection is the contrast between goals (Ragin 1987). Case-oriented strategies are distinctive in that they are centrally concerned with making sense of a relatively small number of cases, selected because they are substantivelyortheoreticallysignificantinsomeway(Eckstein 1975). Conventional variable-oriented strategies, by contrast, are centrally concerned with the problem of assessing the relationship between aspects of cases across a large number of generic ‘observations,’ usually with the goal of inferring general patterns that hold for a population. For example, a researcher might use a case-oriented approach in order to study a small number of firms in an in-depth manner. Suppose these firms were all thought to be unusually successful in retaining their best employees while at the same time investing in them and thus enhancing their potential value to competing firms. To find out how they do it, a researcher would have to conduct an in-depth study of the firms in question. By contrast, a variable-oriented researcher might study the predictors of variation in rates of ‘employee retention’ across a large sample of firms. Is it more a matter of firm or industry characteristics? Do these two sets of factors interact? Useful answers to these questions would be based on careful analysis of relationships between variables, using data drawn from a survey of a large number of firms—the more (and the more varied), the better. As these two examples show, what matters most is the researcher’s starting point: does the researcher seek to understand specific cases or to document general patterns characterizing a population? This contrast follows a longstanding division in all of science, not just social science. Georg Henrik von Wright argues in Explanation and Understanding (1971) that there are two main traditions in the history of ideas regarding the conditions an explanation must satisfy in order to be considered scientifically respectable. One tradition, which he calls ‘finalistic,’ is anchored in the problem of making facts understandable. The other is called ‘causal-mechanistic’ and is anchored in the problem of prediction. The contrast between case-oriented and variable-oriented research closely parallels this fundamental division. In the two examples just described, the first researcher uses the case-oriented approach in order to make certain facts understandable, for example, the spectacular success of a handful of firms in retaining their most valuable employees; the second researcher uses the variableoriented approach in order to derive an equation predicting levels of retention, based on a large sample of firms, and to draw inferences from this equation to an entire population. Once the distinction between case-oriented and variable-oriented research is established and their contrasting goals acknowledged, it is clear that the importance of techniques of data collection as bearers of the ‘case-oriented vs. variable-oriented’ distinction begins to fade. For example, it is clear that a researcher using case-oriented methods to study a handful of firms might benefit from conducting surveys of their employees and performing a conventional variable-oriented analysis of these data. The results of the survey would contribute to this researcher’s depth of knowledge about the firms in question, just as interviewing their top executives or studying their archives would contribute useful information. Likewise, it is clear that the researcher using variableoriented methods to predict rates of retention could benefit from interviews of top executives or personnel 1519
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