Case Study: Logic

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Case Study: Methods and Analysis There is potential for confusion among the terms ‘comparative methods,’ ‘case study methods,’ and ‘qualitative methods.’ In one view the comparative method, or the use of comparisons among a small number of cases, is distinct from the case study method, which in this view involves the internal examination of single cases (see Comparatie Studies: Method and Design). For the present purposes, however, case study methods are defined to include both within-case analysis of single cases and comparisons between or among a small number of cases. This is not an effort to claim wider meaning for the term ‘case studies,’ but an outgrowth of the growing consensus that the strongest means of drawing inferences from case studies is the use of a combination of within-case analysis and cross-case comparisons within a single study or research program, although single case studies can also play a role in theory development. As for the term ‘qualitative methods,’ this is sometimes used to encompass both case studies carried out with a positivist view of the philosophy of science and those implemented with a postmodern or interpretive view. Thispresentarticlehewstothetraditionalterminology in focusing on ‘case studies’ as that subset of qualitative methods that has adopted a largely positivist framework. 2. The Historical Deelopment of Case Study Methods Case study methods have developed through several phases over the last three decades. Prior to the 1970s, ‘case studies’ consisted primarily of historical studies of particular events, countries, or phenomena, with littleeffort to cumulateresults or progressively develop theories (Verba 1967). Throughout the 1970s, however, scholars who were dissatisfied with the state of case study methods, and encouraged by the example of the formalization of statistical methods, began to formalize case study methods. First, Adam Przeworski and Henry Teune (1970) clarified the logic of ‘most similar’ and ‘least similar’ case comparisons. In the former comparison, which draws on the logic of John Stuart Mill’s method of difference and mimics the experimental method, the researcher compares two cases that are similar in all but one independent variable and that differ in the outcome variable. Such a comparison may be consistent with the inference that the difference in the single independent variable that varies between the cases accounts for the difference in the dependent variable (although for a variety of reasons discussed below, this inference may be spurious). In a comparison of least similar cases, which draws on Mill’s method of agreement, the researcher compares two cases that differ in all but one independent variable but that have the same value on the dependent variable. If, Table 1 Types of case studies Lijphart Eckstein atheoretical configurative-ideographic interpretative disciplined-configurative hypothesis generating heuristic deviant ? theory-confirming infirming crucial, most-likely, least-likely for example, we find that teenagers are ‘difficult’ in both tribal societies and industrialized societies, we might be tempted to infer that it is the nature of teenagers rather than the nature of society that accounts for the difficulty of teenagers. Arend Lijphart (1971) and Harry Eckstein (1975) contributed further to the formalization of case study methods by clarifying the differences among various types of case study research designs and theorybuilding goals. These authors identified similar types, although their terminology differs and Lijphart adds an important type, the ‘deviant case,’ for which Eckstein does not make explicit provision. Their types of case studies correspond as shown in Table 1. The atheoretical or configurative-ideographic case study takes the form of a detailed narrative or ‘story’ presented in the form of a chronicle that purports to illuminate how an event came about. Such a narrative is highly specific and makes no explicit use of theory or theory-related variables. Most case studies, however, do have an explanatory purpose. These studies generally fall into the category of ‘disciplined-configurative’ or ‘interpretive’ case studies, in which general propositions are used, often implicitly, to explain specific historical cases. Another variant of such case studies is the use of cases as examples that illustrate a theory. Heuristic case studies seek to generate new hypotheses inductively from the study of particular cases. Notably, statistical methods lack this capacity for inductively generating hypotheses, and they typically rely instead on hypotheses derived deductively or borrowed from case study research. An especially important type of case study for developing new hypotheses is the ‘deviant’ case study. This is the study of a case whose outcome is not predicted or explained adequately by existing theories. Unless the outcome of a deviant case turns out to be a consequence of measurement error, the case is likely to be useful for identifying variables that have been left out of existing theories. Finally, researchers can use case studies to test whether the outcomes and processes that theories predict in particular cases are in fact evident. Eckstein’s and Lijphart’s contributions demonstrated that there was not just a single type of case study, but many kinds of case study research designs and many different theory-building purposes that they 1514
Case Study: Methods and Analysis could serve. Their treatments differed, however, in that Lijphart relied greatly on statistical concepts and language. He was thus skeptical of the value of single case studies for building social science theories, and, consistent with the widespread preference at the time for ‘large N’ over ‘small n’ methods, he urged researchers to consider several means of either decreasing the number of variables in their models or increasing the number of cases to be studied in order to make use of statistical rather than case study methods. This advice, however, raised the risk ‘conceptual stretching’ (Sartori 1970), or of lumping together dissimilar cases under the same definitions. Possibly for this reason, Lijphart later placed greater emphasis instead on the controlled comparison of most similar to cases as a basis for causal inference (Lijphart 1975, Collier 1993). Eckstein, in contrast, focused on the use of case studies for theory testing and argued that even single case studies could provide tests that might strongly support or impugn theories. In so doing, Eckstein developed the idea of a ‘crucial case,’ or a case that ‘must closely fit a theory if one is to have confidence in thetheory’svalidity,or,conversely,mustnotfitequally well any rule contrary to that proposed’ (Eckstein 1975, his emphasis). Eckstein argued that true crucial cases are rare, so he pointed to the alternative of ‘most likely’ and ‘least likely’ cases. A most likely case is one that is almost certain to fit a theory if the theory is true for any cases at all. The failure of a theory to explain a most likely case greatly undermines our confidence in the theory. A least likely case, conversely, is a tough test for a theory because it is a case in which the theory makes only a weak prediction. A theory’s ability to explain a least likely case is strong evidence in favor of the theory. In this way, Eckstein argued, even single case studies could greatly increase or decrease our confidence in a theory or require that we alter its scope conditions. Alexander George (1979a, 1979b) further developed case study methods by refining ‘within-case’ analysis and cross-case comparisons in ways that help each method compensate for the limits of the other. George argued, as Mill himself had, that the ‘method of difference’ and the corresponding practice of comparison of most similar cases could lead to spurious inferences. One reason for this is that no two nonexperimental cases achieve the ideal of being similar in all respects but one independent variable and the outcome. Thus, there is always the danger that left-out variables or residual differences in the values of the independent variables account for the difference in the outcomes of similar cases of (see Human– Enironment Relationship: Comparatie Case Studies). In addition, as Mill recognized, phenomena might be characterized by what general systems theorists have termed ‘equifinality,’ or the condition in which the same outcome can arise through different causal pathways or combinations of variables. Thus, there might be no single necessary or sufficient variable for a phenomenon: it might be that either ABC or DEF causes Y, and that none of the variables A–F is itself sufficient to cause Y (see Human–Enironment Relationship: Comparatie Case Studies). In such circumstances, pair-wise comparisons of cases might wrongly reject variables that contribute to the outcome of interest in conjunction with some contexts but not with others, and might also accept as causal variables that are in fact spurious. To compensate for these limits of controlled comparison, George developed the ‘within case’ methods of ‘congruence testing’ and ‘process tracing’ as means of checking on whether inferences arrived at through case comparisons were spurious (see Pattern Matching: Methodology). In congruence testing, the researcher checks whether the prediction a theory makes in a case, in view of the values of the case’s independent variables, is congruent with the actual outcome in the case. In process tracing, the researcher examines whether the causal process a theory hypothesizes in a case is in fact evident in the sequence and values of the intervening variables in that case. Thus, process tracing might be used to test whether the residual differences between two similar cases were causal or spurious in producing a difference in these cases’ outcomes. Process tracing can perform a heuristic function as well, generating new variables or hypotheses on the basis of sequences of events observed inductively in cases. George (1979a, 1979b) also systematized case study procedures by developing what he called the method of ‘structured focused comparison.’ In this method, the researcher systematically: (a) specifies the research problem and the class of events to be studied; (b) defines the independent, dependent, and intervening variables of the relevant theories; (c) selects the cases to be studied and compared; (d) decides how best to characterize variance in the independent and dependent variables; and (e) formulates a detailed set of standard questions to be applied to each case. In addition, consistent with his emphasis on equifinality, George argued that case studies could be especially useful in developing what he called ‘typological theories,’ or contingent generalizations on ‘the ariety of different causal patterns that can occur for the phenomena in question … [and] the conditions under which each distinctie type of causal patterns occurs’ (George 1979a, his emphasis). He thus advocated a kind of ‘building block’ approach to the development of theories in which each case, while rendered in terms of theoretical variables, might prove to be a distinctive causal pathway to the outcome of interest. In the 1980s and 1990s, thousands of books and articles made use of these improvements in case study methods in a wide variety of social science research programs.Meanwhile,scholarscontinuedto elaborate case study methods and articulate the ways in which they differed from statistical methods. David Collier, 1515
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