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Deviant Case Analysis

Deviant case analysis is a methodological approach that is an outcome of a researcher's sampling decisions and treatment of data. Sometimes referred to as negative case analysis, the approach is based on the view that any findings generated from data should be able to explain a wide range of observations. This provides both the opportunity for finding novel theoretical relationships as well as confidence that a study has been conducted in a rigorous way.

Conceptual Overview and Discussion

The idea that deviant cases are important to carefully examine is embedded in many of the qualitative approaches that are widely used in case study research. One of the central features of grounded theory is the constant comparative method of data analysis, the process by which theoretical ideas are revised and redesigned as data are compared with them. In this way, data are organized and compared with the theoretical relationships contained in the data, being constantly adjusted for new data that are collected. If these new data do not conform to the theoretical relationships present in earlier data, then new relationships are developed that account for all available data. The result is a condition of theoretical saturation, the signal that theory has been developed using the full range of data collected. The deviant or negative case study therefore provides the opportunity for a more robust theory, one that explains the unexpected or atypical as well as it explains the expected or typical.

Choosing to include deviant cases in research is therefore a matter of sampling, something that matters to all qualitative researchers. David Silverman provides a comprehensive treatment of the decisions that go into selecting a case. He suggests that although some researchers may be content to provide a purely descriptive account of a phenomenon with no regard for generalizability, most are not. Instead, a hallmark of good qualitative research is that it produces explanations, for example, why something happens or under what conditions it happens. These types of explanations lend themselves to discussions of generalizability, usually couched in terms of transferability of findings or resonance of findings in contexts other than the one researched. As such, there is an issue of representativeness embedded in all qualitative or case study research that sampling can, to a certain extent, address.

Application

Sampling in qualitative research is typically explained in theoretical or purposive terms; in other words, what should determine the choice to study a particular case or set of respondents? Purposive sampling is guided by the desire to have a case illustrate phenomena of interest. This requires careful thought on the part of the researcher to determine the people from whom and places where useful data can be obtained. When these decisions are theoretically determined, the term theoretical sampling is used. It is primarily concerned with choosing a sample that will contain data suitable for answering research questions and allowing for the construction of convincing interpretations of these data. At some level, researchers are advised to choose any research setting that is easily accessible and will provide the data needed for their study. It is at this point that researchers should attempt to include deviant cases in their research, lest they select only cases that conform to their a priori expectations. By actively seeking out deviant or negative cases, researchers increase the likelihood of creating a robust set of findings that have relevance in a wide range of contexts.

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